Radar Dish. Armature controlled dc motor. Inside. θ r input. Outside. θ D output. θ m. Gearbox. Control Transmitter. Control. θ D.

Size: px
Start display at page:

Download "Radar Dish. Armature controlled dc motor. Inside. θ r input. Outside. θ D output. θ m. Gearbox. Control Transmitter. Control. θ D."

Transcription

1 Radar Dish ME 304 CONTROL SYSTEMS Mechanical Engineering Deartment, Middle East Technical University Armature controlled dc motor Outside θ D outut Inside θ r inut r θ m Gearbox Control Transmitter θ D dc amlifier Control Transformer Prof. Dr. Y. Samim Ünlüsoy Prof. Dr. Y. Samim Ünlüsoy 1

2 COURSE OUTLINE I. INTRODUCTION & BASIC CONCEPTS II. MODELING DYNAMIC SYSTEMS III. CONTROL SYSTEM COMPONENTS IV. STABILITY V. TRANSIENT RESPONSE VI. STEADY STATE RESPONSE VII. DISTURBANCE REJECTION CH VIII VIII. CONTROL ACTIONS & CONTROLLERS IX. FREQUENCY RESPONSE ANALYSIS X. SENSITIVITY ANALYSIS xi. ROOT LOCUS ANALYSIS Prof. Dr. Y. Samim Ünlüsoy 2

3 CONTROL ACTIONS & CONTROLLERS OBJECTIVES In this chater : Basic control actions and controllers, and their characteristics ti will be examined. Their alications will be introduced. Prof. Dr. Y. Samim Ünlüsoy 3

4 CONTROL ACTIONS & CONTROLLERS A controller is a device which roduces a control signal that results in the reduction of the deviation of controlled outut from the desired value. Prof. Dr. Y. Samim Ünlüsoy 4

5 CONTROL ACTIONS & CONTROLLERS The inut to the controller is the actuating error E a (s), which is the difference between the system resonse B(s), as measured by a sensor, and the reference signal R(s), which reresents the desired d system resonse. R(s) + E a (s) M(s) C(s) Controller G(s) - B(s) H(s) Prof. Dr. Y. Samim Ünlüsoy 5

6 CONTROL ACTIONS & CONTROLLERS Controller roduces the maniulated inut at its outut to be alied to the actuator. t R(s) + - E a (s) Controller M(s) G(s) C(s) B(s) H(s) Prof. Dr. Y. Samim Ünlüsoy 6

7 CONTROL ACTIONS & CONTROLLERS A controller is required to shae the error signal such that certain control criteria or secifications, are satisfied. These criteria may involve : - Transient resonse characteristics, -Steady-state error, - Disturbance rejection, - Sensitivity to arameter changes. Prof. Dr. Y. Samim Ünlüsoy 7

8 CONTROL ACTIONS & CONTROLLERS Basic Control Actions : A controller roduces a control signal (maniulated inut) according to its inut which is the actuating error. The algorithm that relates the error and the control signal is called the control action (law)(strategy). Control Action Actuating error Controller Control signal Prof. Dr. Y. Samim Ünlüsoy 8

9 CONTROL ACTIONS & CONTROLLERS The most commonly used Control Actions are : 1. Two osition (on-off, off, bang-bang), bang), 2. Proortional (P-control), 3. Derivative (D-control), 4. Integral (I-control). Controllers to rovide these control actions (with the excetion of D-control) and the combinations of the last three are commercially available. Prof. Dr. Y. Samim Ünlüsoy 9

10 TWO POSITION CONTROL (Ogata ) 64) Two Position Control For this tye of control, the outut of the controller can have only one of the two ossible values, M or M 1 2. e(t) M 1 m(t ) M 2 e(t) controller m(t) m(t)= M1 for e(t)>0 M2 for e(t)<0 Prof. Dr. Y. Samim Ünlüsoy 10

11 TWO POSITION CONTROL The value of M 2 either is usually i) zero, in which case the e(t) M 1 m(t) controller is called the 0 on-off off controller, or On-off controller ii) equal to -M 1, in which M case, the controller is e(t) m(t) called the bang-bang -M controller. Bang-bang controller Prof. Dr. Y. Samim Ünlüsoy 11

12 TWO POSITION CONTROL In ractice, the two osition controllers exhibit somewhat significant hysteresis (usually due to friction), sometimes introduced intentionally to revent remature wear-out of the switching hardware. In this case the outut e(t) 1 m(t) switches to M only 1 M after the actuating error 2 becomes ositive by an amount d. Similarly it Differential ga switches back to M only 2 after the actuating error becomes equal to -d. M 1 d Prof. Dr. Y. Samim Ünlüsoy 12

13 TWO POSITION CONTROL The existence of a differential ga reduces the accuracy of the control system, but it also reduces the frequency of switching which results in longer oerational life. e(t) M 1 m(t) M 2 Differential ga Prof. Dr. Y. Samim Ünlüsoy 13

14 TWO POSITION CONTROL EXAMPLE a Consider the water level control system illustrated in the figure. Solenoid valve Inut Switch + _ v q i h Float R C q o Prof. Dr. Y. Samim Ünlüsoy 14

15 TWO POSITION CONTROL EXAMPLE b Assume at first that the tank is emty. In this case, the solenoid will be energized oening the valve fully. h R Hence rovided that q >q i o, the water level will rise. q i C + _ v q o dh q-q i o =C h=rqo dt RC dh dt +h=rq i Prof. Dr. Y. Samim Ünlüsoy 15

16 TWO POSITION CONTROL EXAMPLE c The system is of first order and the variation of water level versus time is shown by the filling curve. h(t) Filling curve (q i >q o ) Emtying curve (q i =0) RC dh dt +h=rq i t If, at some time t o, the solenoid is de-energized energized closing the valve comletely, q i =0, then the water in the tank will drain off. The variation of the water level in the tank is now shown by the emtying curve. dh RC +h= 0 dt Prof. Dr. Y. Samim Ünlüsoy 16

17 TWO POSITION CONTROL EXAMPLE d If the switch is adjusted for a desired water level, the inut q i will be on or off (either a ositive constant or zero) deending on the difference between the desired and the actual water levels. If the clearances and friction in the ivot oints are considered, the switching characteristics are likely to have a certain amount of differential ga. q i 2d e(t)=h d -h Prof. Dr. Y. Samim Ünlüsoy 17

18 TWO POSITION CONTROL EXAMPLE e Therefore during the actual oeration, inut will be on until the water level exceeds the desired level by half the differential ga. h d q i 0 h(t) 2d Filling curve Emtying (q i >q o ) curve (q i =0) Then the solenoid valve will be shut off until the water level dros below the desired level by half the differential ga. The water level will continuously oscillate about the desired level. t Prof. Dr. Y. Samim Ünlüsoy 18

19 TWO POSITION CONTROL EXAMPLE f It should be noted that, the smaller the differential ga is, the smaller is the deviation from the desired level. But on the other hand, the number of switch on and off s increases. Differential ga small large Δt Prof. Dr. Y. Samim Ünlüsoy 19

20 PROPORTIONAL CONTROL Ogata.65 Proortional Control (P-control) With this tye of control action, a control signal roortional to error signal is roduced. m(t)=k e (t) a M(s) =K E (s) a R(s) + E a (s) M(s) C(s) K G(s) - B(s) H(s) K : roortional gain. Prof. Dr. Y. Samim Ünlüsoy 20

21 PROPORTIONAL CONTROL A roortional controller is essentially an amlifier with an adjustable gain. The value of K should be selected to satisfy the requirements of stability, accuracy, and satisfactory transient resonse, as well as satisfactory disturbance rejection characteristics. Prof. Dr. Y. Samim Ünlüsoy 21

22 PROPORTIONAL CONTROL In general, For small values of K, the corrective action is slow articularly for small errors. For large values of K, the erformance of the control system stem is imroved. But this may lead to instability. Usually, a comromise is necessary in selecting a roer gain. If this is not ossible, then roortional control action is used with some other control action(s). Prof. Dr. Y. Samim Ünlüsoy 22

23 DERIVATIVE CONTROL Derivative Control (D-control) In this case the control signal of the controller is roortional to the derivative (sloe) of the error signal. m(t)=kk d de (t) () a dt M(s) =Kd s E (s) a Derivative control action is never used alone, since it does not resond to a constant error, however large it may be. K d : derivative gain (adjustable). Prof. Dr. Y. Samim Ünlüsoy 23

24 DERIVATIVE CONTROL Derivative control action resonds to the rate of change of error signal and can roduce a control signal before the error becomes too large. As such, derivative control action anticiates the error, takes early corrective action, and tends to increase the stability of the system. Prof. Dr. Y. Samim Ünlüsoy 24

25 DERIVATIVE CONTROL Derivative control action has no direct effect on steady state t error. But it increases the daming in the system and allows a higher value for the oen loo gain K which reduces the steady state error. Prof. Dr. Y. Samim Ünlüsoy 25

26 DERIVATIVE CONTROL Derivative control, however, has disadvantages d as well. It amlifies noise signals coming in with the error signal and may saturate the actuator. It cannot be used if the error signal is not otd differentiable. e tabe Thus derivative control is used only together with some other control action! Prof. Dr. Y. Samim Ünlüsoy 26

27 INTEGRAL CONTROL Ogata.65 Integral Control (I-control) With this tye of control action, control signal is roortional to the integral of the error signal. M(s) K = m(t)= K i e (t)dt a E (s) a s i R(s) + E a (s) K M(s) C(s) i G(s) - s B(s) H(s) K i : integral gain (adjustable). Prof. Dr. Y. Samim Ünlüsoy 27

28 INTEGRAL CONTROL It is obvious that even a small error can be detected, t d since integral control roduces a control signal roortional to the area under the error signal. Hence, integral control increases the accuracy of the system. Integral control is said to look at the ast of the error signal. e(t) Large error Small error small area large area t Prof. Dr. Y. Samim Ünlüsoy 28

29 INTEGRAL CONTROL Remember that each s term in the denominator of the oen loo transfer function increases the tye of the system by one, and thus reduces the steady state error. The use of integral controller will increase the tye of the oen loo transfer function by one. Note, however, that for zero error signal, the integral control may still roduce a constant control signal which may in turn lead to instability. Prof. Dr. Y. Samim Ünlüsoy 29

30 PROPORTIONAL + DERIVATIVE (PD) CONTROL Control action with roortional + derivative (PD) control is given by m(t)=k e(t)+k T d de(t) M(s) =K E(s) ( ) dt 1+T d s R(s) + - E(s) K ( 1+T s) d M(s) G(s) C(s) B(s) H(s) T d : derivative time. Prof. Dr. Y. Samim Ünlüsoy 30

31 PROPORTIONAL + INTEGRAL (PI) CONTROL Control action with roortional + integral (PI) control is given by m(t)=k e(t)+k 1 T i e(t)dt M(s) 1 =K 1+ E(s) Ti s R(s) + - E(s) K 1 1+ Ts i M(s) G(s) C(s) T i B(s) H(s) : integral time Prof. Dr. Y. Samim Ünlüsoy 31

32 PROPORTIONAL + INTEGRAL + DERIVATIVE (PID) CONTROL Control action with roortional + integral + derivative (PID) control is given by K de(t) m(t)=ke(t)+kt d + e(t)dt dt T i R(s) + E(s) 1 M(s) K 1+T d s+ - Ts i M(s) 1 =K 1+Tds+ E(s) T i s B(s) H(s) Prof. Dr. Y. Samim Ünlüsoy 32

33 REALIZATION OF CONTROLLERS Comonents in most control systems can be mechanical, electrical, hydraulic or neumatic. In some cases, sensors, controllers, and actuators may be obtained from combinations such as electro- mechanical or electro-hydraulic comonents. See Ogata for various realizations of electrical, hydraulic, and neumatic controllers. Prof. Dr. Y. Samim Ünlüsoy 33

34 CONTROL ACTIONS - Proortional Control Position Control of an Inertial Load θ r (s) + - Disturbance Controller + + K + - Dc motor+load C 1 Js+b s θ(s) K b K : motor torque constant, t R a : armature resistance, C=K/ R a K b : motor back emf constant, J : motor + load inertia, b : viscous daming coefficient. Prof. Dr. Y. Samim Ünlüsoy 34

35 CONTROL ACTIONS - Proortional Control Initially neglect disturbance, i.e. D(s)=0. θ r (s) + - Controller K + - Dc motor+load C 1 Js+b s θ(s) K b KC θ(s) = J θ r(s) 2 b+k K C bc s + s+ J J 2 K C b+k bc ω n = 2ξω n= J J b+kbc 1 ξ = 2 JC K Prof. Dr. Y. Samim Ünlüsoy 35

36 2 KC n ω = J b+kbc 1 Proortional Control CONTROL ACTIONS ξ = 2 JC K β ω t It is noted that increasing r the roortional gain : i) Undamed natural t frequency of the system is increased, thus the seed of resonse is increased. π β 1 d = β= tan ω ξω d π = ω 2 ω =ω ξ d d n 1 n ξ -π ξ 1-ξ 2 M =e ii) The daming ratio is decreased, thus the relative stability of the system is ts ( 5% ) reduced. Note : ξω n 3 t 5% = ξωn 4 t 2% = ξωn is not affected by K! s ( ) Prof. Dr. Y. Samim Ünlüsoy 36

37 CONTROL ACTIONS - Proortional Control Now, let us examine the steady state resonse. θ r (s) + - Controller K + - Dc motor+load C Js+b 1 s θ(s) K b θ r (s) + - Js 2 K C ( ) + b+k C s b θ(s) Oen loo transfer function : K C G(s)= s Js+ b+k b C ( ) Prof. Dr. Y. Samim Ünlüsoy 37

38 CONTROL ACTIONS - Proortional Control Classify the oen loo transfer function. First convert to standard form. KC G(s)= s Js+ b+kb C Thus, ( ) System tye is 1. The oen loo gain is KC b+kbc G(s)= J s s+1 b+kb C KC K= b+k C b Prof. Dr. Y. Samim Ünlüsoy 38

39 CONTROL ACTIONS - Proortional Control System tye is 1. The oen loo gain is K C K= b+k C b Thus the steady state t error due to unit ste inut will be zero. The steady state error due to unit ram inut will be finite. 1 b+kbc 1 e ss = = K C K The steady state error due to unit ram inut can be minimized by using a larger value of the roortional gain. Prof. Dr. Y. Samim Ünlüsoy 39

40 CONTROL ACTIONS - Proortional Control Now let us consider disturbance inut only. Disturbance Controller K Dc motor+load C Js+b K b 1 s θ(s) D(s) + - Js 2 C ( ) + b+k C s b θ(s) In this case, the outut itself K will be the error. Prof. Dr. Y. Samim Ünlüsoy 40

41 CONTROL ACTIONS - Proortional Control In this case, the outut itself will be the error. D(s) C θ(s) ) 2 Js + + ( b+kbc) s - K C 1 1 e ss=lims 0s = 2 ( ) b s K Js + b+k C s+kc It is observed that for minimum steady state error due to a ste disturbance, and a ram inut, K must be as large as stability requirements allow. Prof. Dr. Y. Samim Ünlüsoy 41

42 CONTROL ACTIONS Proortional + Derivative Control If a roortional + derivative controller is used : θ r (s) + - Controller ( ) K T s+1 d Disturbance + + Js Dc motor+load 2 C ( ) + b+k C s b θ(s) Neglecting disturbance ( ) θ(s) K C T s+1 = θ (s) Js + b+k C+K T C s+k C d θ (s) 2 disturbance r ( ) b d Prof. Dr. Y. Samim Ünlüsoy 42

43 CONTROL ACTIONS Proortional + Derivative Control KC 1+T d s ( ) θ(s) = J θ r (s) 2 b+kb C+K Td C K C s + s+ J J Note that : 2 KC n ω = J ( ) 2ξω = n b+ K b+ktd C b+k CK bc 1 1 ξ = + T 2 JC K 2 J Derivative control does not affect the undamed natural frequency. (Meaning?) Derivative time T d can be selected to imrove daming ratio. J d Prof. Dr. Y. Samim Ünlüsoy 43

44 CONTROL ACTIONS Proortional + Derivative Control ( ) ( ) K C 1+T s K C 1+T ds b+kbc G(s)= = s Js+ ( b+kbc) J s s+1 b+kb C System tye is still 1, thus the steady state error for unit ste inut is zero. The steady state error for unit ram inut is given as : d 1 b+kbc 1 e ss= = K C K Therefore, the derivative control has no effect on the steady state error. Prof. Dr. Y. Samim Ünlüsoy 44

45 CONTROL ACTIONS Proortional + Derivative Control If the disturbance is taken to be the only inut, then the outut θ(s) will be the error. D(s) + - Js Dc motor+load 2 C ( ) + b+k C s b ( ) K T s+1 d Controller θ(s) C 1 1 e ss =lims 0s = 2 Js + ( b+k ) s K bc+ktdc s+kc Prof. Dr. Y. Samim Ünlüsoy 45

46 CONTROL ACTIONS Proortional + Derivative Control It is observed that, if the disturbance is taken to be the only inut, the steady state error (equal to the steady state value of the outut) for a unit ste inut also is unaffected by the inclusion of the derivative control. e ss unit ste 1 = K Prof. Dr. Y. Samim Ünlüsoy 46

47 CONTROL ACTIONS Proortional + Derivative Control In conclusion, the addition of derivative control action to roortional control action - is useful to rovide additional control on daming and hence imroves relative stability, - has no direct effect on steady state error. It may, however, be useful in reducing steady state error indirectly by allowing the use of larger values of K without causing stability roblems. Prof. Dr. Y. Samim Ünlüsoy 47

48 CONTROL ACTIONS Velocity (Tachometer ) Feedback Velocity or tachometer feedback can be emloyed together with roortional control to rovide characteristics similar to that of PD-control. θ r (s) + _ Controller Disturbance + K + _ Dc motor+load C Js+ b+k C ( ) b 1 s θ(s) K t Tachometer Prof. Dr. Y. Samim Ünlüsoy 48

49 CONTROL ACTIONS Velocity (Tachometer ) Feedback Consider the case without disturbance. Controller Dc motor+load θ r (s) θ(s) + C 1 ( ) K Js+ ( b+k ) s - - bc Kt Tachometer θ(s) K C = θ (s) 2 Js + b+k C+K K C s+k C ( ) r b t Prof. Dr. Y. Samim Ünlüsoy 49

50 CONTROL ACTIONS Velocity (Tachometer ) Feedback Clearly, if you relace T by K d t, the characteristic equation is of the same form as that of the PD-control case. Thus the undamed natural frequency and daming ratio exressions are again the same, if one relaces T by d K t. KC θ(s) = 2 ( ) θ (s) Js + b+k C+K K C s+k C r b t 2 KC b+kbc 1 1 CK ω n = ξ = + K J 2 JC K 2 J t Prof. Dr. Y. Samim Ünlüsoy 50

51 CONTROL ACTIONS Velocity (Tachometer ) Feedback KC KC b+kbc+kktc G(s)= ( ) b t = s Js+ b+k C+K K C J s s+1 b+kbc+kktc System tye is 1, thus the steady state error for unit ste inut is zero. The steady state error for unit ram inut is given as : 1 b+k bc+k K tc 1 b+k b C 1 e ss= = = +K K C K C K t Prof. Dr. Y. Samim Ünlüsoy 51

52 CONTROL ACTIONS Velocity (Tachometer ) Feedback Now let us consider disturbance inut only. - Disturbance Controller + K - + Dc motor+load C Js+ ( b+kbc) 1 s θ(s) Kt Tachometer D(s) + - Js 2 K C ( ) + b+k C s b ( 1+K s) t θ(s) In this case, the outut itself will be the error. Prof. Dr. Y. Samim Ünlüsoy 52

53 CONTROL ACTIONS Velocity (Tachometer ) Feedback In this case, D(s) C θ(s) the outut 2 Js + itself will be + ( b+kbc) s - the error. K ( 1+K s) C 1 1 e ss=lims 0s = 2 Js + b+c( K ) b +K Kt s+k C s K It is observed that disturbance resonse of roortional control + velocity feedback is the same as that of roortional + derivative control. t Prof. Dr. Y. Samim Ünlüsoy 53

54 CONTROL ACTIONS Proortional + Integral Control If a roortional + integral controller is used : θ r (s) + - Disturbance Controller Dc motor+load + 1 C θ(s) K 1+ Ts 2 i + Js + ( b+kbc) s θ(s) KC( Ts+1 i ) = 3 2 disturbance ( ) Neglecting disturbance θ (s) TJs +b+k Cs +K TC Cs+K C r i b i Prof. Dr. Y. Samim Ünlüsoy 54

55 CONTROL ACTIONS Proortional + Integral Control K C( Ts i +1 ) ( ) θ(s) = θ (s) T Js +T b+k C s +K T Cs+K C 3 2 r i i b i Note that : Addition of integral control action to roortional control action increases the order of the system. Thus, transient and steady resonse as well as the stability and disturbance rejection characteristics of the system will be changed. Prof. Dr. Y. Samim Ünlüsoy 55

56 CONTROL ACTIONS Proortional + Integral Control ( ) ( ) K C Ts+1 G(s)= = 2 s Ti Js+ b+kbc ( i ) ( ) K C Ts+1 T b+k C i i b 2 J s s+1 b+kb C System tye is now 2, thus the steady state error for unit ste and ram inuts are zero. The steady state error for unit acceleration inut is given as : ( ) 1 Ti b+kbc 1 e ss= = K C K Therefore, the integral control can be used to reduce steady state error. Prof. Dr. Y. Samim Ünlüsoy 56

57 CONTROL ACTIONS Proortional + Integral Control If the disturbance is taken to be the only inut, then the outut θ(s) will be the error. Dc motor+load D(s) C 2 Js ( ) + b - K + b+k C s 1 1+ Ts i Controller θ(s) TCs i 1 e ss =lims 0s = ( ) TJs i +Ti b+kbc s +K s TCs+K i C TCs i 1 e ss =lims 0s = TJs i +Ti( b+kbc) s +KTCs+K i C s T K i Prof. Dr. Y. Samim Ünlüsoy 57

58 CONTROL ACTIONS Proortional + Integral Control If the disturbance is taken to be the only inut, the steady state error (equal to the steady state value of the outut) for a unit ste disturbance inut is zeroed and the steady state error for a unit ram disturbance inut becomes finite by the inclusion of the integral control. e =0 ss ste e ss unit ram T = K i Prof. Dr. Y. Samim Ünlüsoy 58

59 CONTROL ACTIONS Proortional + Integral Control In conclusion, it is observed that the addition of integral control action to roortional control action - is useful in reducing the steady state error by increasing the tye of the oen loo transfer function by one, -changes the transient resonse characteristics of the system by increasing the order of the system, making the system more suscetible to instability. Prof. Dr. Y. Samim Ünlüsoy 59

Radar Dish. Armature controlled dc motor. Inside. θ r input. Outside. θ D output. θ m. Gearbox. Control Transmitter. Control. θ D.

Radar Dish. Armature controlled dc motor. Inside. θ r input. Outside. θ D output. θ m. Gearbox. Control Transmitter. Control. θ D. Radar Dish ME 304 CONTROL SYSTEMS Mechanical Engineering Department, Middle East Technical University Armature controlled dc motor Outside θ D output Inside θ r input r θ m Gearbox Control Transmitter

More information

Oil Temperature Control System PID Controller Algorithm Analysis Research on Sliding Gear Reducer

Oil Temperature Control System PID Controller Algorithm Analysis Research on Sliding Gear Reducer Key Engineering Materials Online: 2014-08-11 SSN: 1662-9795, Vol. 621, 357-364 doi:10.4028/www.scientific.net/kem.621.357 2014 rans ech Publications, Switzerland Oil emerature Control System PD Controller

More information

Radar Dish. Armature controlled dc motor. Inside. θ r input. Outside. θ D output. θ m. Gearbox. Control Transmitter. Control. θ D.

Radar Dish. Armature controlled dc motor. Inside. θ r input. Outside. θ D output. θ m. Gearbox. Control Transmitter. Control. θ D. Radar Dish ME 304 CONTROL SYSTEMS Mechanical Engineering Department, Middle East Technical University Armature controlled dc motor Outside θ D output Inside θ r input r θ m Gearbox Control Transmitter

More information

Indirect Rotor Field Orientation Vector Control for Induction Motor Drives in the Absence of Current Sensors

Indirect Rotor Field Orientation Vector Control for Induction Motor Drives in the Absence of Current Sensors Indirect Rotor Field Orientation Vector Control for Induction Motor Drives in the Absence of Current Sensors Z. S. WANG *, S. L. HO ** * College of Electrical Engineering, Zhejiang University, Hangzhou

More information

I Poles & zeros. I First-order systems. I Second-order systems. I E ect of additional poles. I E ect of zeros. I E ect of nonlinearities

I Poles & zeros. I First-order systems. I Second-order systems. I E ect of additional poles. I E ect of zeros. I E ect of nonlinearities EE C28 / ME C34 Lecture Chater 4 Time Resonse Alexandre Bayen Deartment of Electrical Engineering & Comuter Science University of California Berkeley Lecture abstract Toics covered in this resentation

More information

Control of Manufacturing Processes

Control of Manufacturing Processes Control of Manufacturing Processes Subject 2.830 Spring 2004 Lecture #19 Position Control and Root Locus Analysis" April 22, 2004 The Position Servo Problem, reference position NC Control Robots Injection

More information

Control of Manufacturing Processes

Control of Manufacturing Processes Control of Manufacturing Processes Subject 2.830 Spring 2004 Lecture #18 Basic Control Loop Analysis" April 15, 2004 Revisit Temperature Control Problem τ dy dt + y = u τ = time constant = gain y ss =

More information

V. Practical Optimization

V. Practical Optimization V. Practical Otimization Scaling Practical Otimality Parameterization Otimization Objectives Means Solutions ω c -otimization Observer based design V- Definition of Gain and Frequency Scales G ( s) kg

More information

Feedback-error control

Feedback-error control Chater 4 Feedback-error control 4.1 Introduction This chater exlains the feedback-error (FBE) control scheme originally described by Kawato [, 87, 8]. FBE is a widely used neural network based controller

More information

FEEDBACK CONTROL SYSTEMS

FEEDBACK CONTROL SYSTEMS FEEDBAC CONTROL SYSTEMS. Control System Design. Open and Closed-Loop Control Systems 3. Why Closed-Loop Control? 4. Case Study --- Speed Control of a DC Motor 5. Steady-State Errors in Unity Feedback Control

More information

Analysis and Design of Control Systems in the Time Domain

Analysis and Design of Control Systems in the Time Domain Chapter 6 Analysis and Design of Control Systems in the Time Domain 6. Concepts of feedback control Given a system, we can classify it as an open loop or a closed loop depends on the usage of the feedback.

More information

ME 375 System Modeling and Analysis. Homework 11 Solution. Out: 18 November 2011 Due: 30 November 2011 = + +

ME 375 System Modeling and Analysis. Homework 11 Solution. Out: 18 November 2011 Due: 30 November 2011 = + + Out: 8 November Due: 3 November Problem : You are given the following system: Gs () =. s + s+ a) Using Lalace and Inverse Lalace, calculate the unit ste resonse of this system (assume zero initial conditions).

More information

Process Control J.P. CORRIOU. Reaction and Process Engineering Laboratory University of Lorraine-CNRS, Nancy (France) Zhejiang University 2016

Process Control J.P. CORRIOU. Reaction and Process Engineering Laboratory University of Lorraine-CNRS, Nancy (France) Zhejiang University 2016 Process Control J.P. CORRIOU Reaction and Process Engineering Laboratory University of Lorraine-CNRS, Nancy (France) Zhejiang University 206 J.P. Corriou (LRGP) Process Control Zhejiang University 206

More information

Acceleration Feedback

Acceleration Feedback Acceleration Feedback Mechanical Engineer Modeling & Simulation Electro- Mechanics Electrical- Electronics Engineer Sensors Actuators Computer Systems Engineer Embedded Control Controls Engineer Mechatronic

More information

Control System (ECE411) Lectures 13 & 14

Control System (ECE411) Lectures 13 & 14 Control System (ECE411) Lectures 13 & 14, Professor Department of Electrical and Computer Engineering Colorado State University Fall 2016 Steady-State Error Analysis Remark: For a unity feedback system

More information

FLOW RATE CONTROL OF VARIABLE DISPLACEMENT PISTON PUMP USING GENETIC ALGORITHM TECHNIQUE

FLOW RATE CONTROL OF VARIABLE DISPLACEMENT PISTON PUMP USING GENETIC ALGORITHM TECHNIQUE FLOW RATE CONTROL OF VARIABLE DISPLACEMENT PISTON PUMP USING GENETIC ALGORITHM TECHNIQUE Ayman A. Aly 1,2 and A. Al-Marakeby 1,3 1) Mechatronics Section, Mech. Eng. Det., Taif University, Taif, 888, Saudi

More information

Statics and dynamics: some elementary concepts

Statics and dynamics: some elementary concepts 1 Statics and dynamics: some elementary concets Dynamics is the study of the movement through time of variables such as heartbeat, temerature, secies oulation, voltage, roduction, emloyment, rices and

More information

Error Analysis for Gyroscopic Force Measuring System

Error Analysis for Gyroscopic Force Measuring System Proceedings of the 7 th International Conference on Force, Mass, Torque and Pressure Measurements, IMEKO TC3, 7- Set., Istanbul, Turkey Error Analysis for Gyroscoic Force Measuring System Shigeru Kurosu

More information

MODELING OF THE DYNAMIC RESPONSE OF A FRANCIS TURBINE

MODELING OF THE DYNAMIC RESPONSE OF A FRANCIS TURBINE MODELING OF THE DYNAMIC RESPONSE OF A FRANCIS TURBINE Paolo PENNACCHI, Steven CHATTERTON *, Andrea VANIA Politecnico di Milano, Deartment of Mechanical Engineering - Via G. La Masa, - 256 - Milano, Italy.

More information

Introduction to MVC. least common denominator of all non-identical-zero minors of all order of G(s). Example: The minor of order 2: 1 2 ( s 1)

Introduction to MVC. least common denominator of all non-identical-zero minors of all order of G(s). Example: The minor of order 2: 1 2 ( s 1) Introduction to MVC Definition---Proerness and strictly roerness A system G(s) is roer if all its elements { gij ( s)} are roer, and strictly roer if all its elements are strictly roer. Definition---Causal

More information

Performance of Feedback Control Systems

Performance of Feedback Control Systems Performance of Feedback Control Systems Design of a PID Controller Transient Response of a Closed Loop System Damping Coefficient, Natural frequency, Settling time and Steady-state Error and Type 0, Type

More information

A PARTICLE SWARM OPTIMIZATION APPROACH FOR TUNING OF SISO PID CONTROL LOOPS NELENDRAN PILLAY

A PARTICLE SWARM OPTIMIZATION APPROACH FOR TUNING OF SISO PID CONTROL LOOPS NELENDRAN PILLAY A PARTICLE SWARM OPTIMIZATION APPROACH FOR TUNING OF SISO PID CONTROL LOOPS NELENDRAN PILLAY 2008 A PARTICLE SWARM OPTIMIZATION APPROACH FOR TUNING OF SISO PID CONTROL LOOPS By Nelendran Pillay Student

More information

Control of Electromechanical Systems

Control of Electromechanical Systems Control of Electromechanical Systems November 3, 27 Exercise Consider the feedback control scheme of the motor speed ω in Fig., where the torque actuation includes a time constant τ A =. s and a disturbance

More information

C(s) R(s) 1 C(s) C(s) C(s) = s - T. Ts + 1 = 1 s - 1. s + (1 T) Taking the inverse Laplace transform of Equation (5 2), we obtain

C(s) R(s) 1 C(s) C(s) C(s) = s - T. Ts + 1 = 1 s - 1. s + (1 T) Taking the inverse Laplace transform of Equation (5 2), we obtain analyses of the step response, ramp response, and impulse response of the second-order systems are presented. Section 5 4 discusses the transient-response analysis of higherorder systems. Section 5 5 gives

More information

Multivariable Generalized Predictive Scheme for Gas Turbine Control in Combined Cycle Power Plant

Multivariable Generalized Predictive Scheme for Gas Turbine Control in Combined Cycle Power Plant Multivariable Generalized Predictive Scheme for Gas urbine Control in Combined Cycle Power Plant L.X.Niu and X.J.Liu Deartment of Automation North China Electric Power University Beiing, China, 006 e-mail

More information

MODELLING, SIMULATION AND ROBUST ANALYSIS OF THE TEMPERATURE PROCESS CONTROL

MODELLING, SIMULATION AND ROBUST ANALYSIS OF THE TEMPERATURE PROCESS CONTROL The 6 th edition of the Interdiscilinarity in Engineering International Conference Petru Maior University of Tîrgu Mureş, Romania, 2012 MODELLING, SIMULATION AND ROBUST ANALYSIS OF THE TEMPERATURE PROCESS

More information

( ) ( = ) = ( ) ( ) ( )

( ) ( = ) = ( ) ( ) ( ) ( ) Vρ C st s T t 0 wc Ti s T s Q s (8) K T ( s) Q ( s) + Ti ( s) (0) τs+ τs+ V ρ K and τ wc w T (s)g (s)q (s) + G (s)t(s) i G and G are transfer functions and independent of the inputs, Q and T i. Note

More information

A Simple Fuzzy PI Control of Dual-Motor Driving Servo System

A Simple Fuzzy PI Control of Dual-Motor Driving Servo System MATEC Web of Conferences 04, 0006 (07) DOI: 0.05/ matecconf/07040006 IC4M & ICDES 07 A Simle Fuzzy PI Control of Dual-Motor Driving Servo System Haibo Zhao,,a, Chengguang Wang 3 Engineering Technology

More information

Design of NARMA L-2 Control of Nonlinear Inverted Pendulum

Design of NARMA L-2 Control of Nonlinear Inverted Pendulum International Research Journal of Alied and Basic Sciences 016 Available online at www.irjabs.com ISSN 51-838X / Vol, 10 (6): 679-684 Science Exlorer Publications Design of NARMA L- Control of Nonlinear

More information

Video 5.1 Vijay Kumar and Ani Hsieh

Video 5.1 Vijay Kumar and Ani Hsieh Video 5.1 Vijay Kumar and Ani Hsieh Robo3x-1.1 1 The Purpose of Control Input/Stimulus/ Disturbance System or Plant Output/ Response Understand the Black Box Evaluate the Performance Change the Behavior

More information

CHBE320 LECTURE XI CONTROLLER DESIGN AND PID CONTOLLER TUNING. Professor Dae Ryook Yang

CHBE320 LECTURE XI CONTROLLER DESIGN AND PID CONTOLLER TUNING. Professor Dae Ryook Yang CHBE320 LECTURE XI CONTROLLER DESIGN AND PID CONTOLLER TUNING Professor Dae Ryook Yang Spring 2018 Dept. of Chemical and Biological Engineering 11-1 Road Map of the Lecture XI Controller Design and PID

More information

Chapter 9 Practical cycles

Chapter 9 Practical cycles Prof.. undararajan Chater 9 Practical cycles 9. Introduction In Chaters 7 and 8, it was shown that a reversible engine based on the Carnot cycle (two reversible isothermal heat transfers and two reversible

More information

Appendix A: Exercise Problems on Classical Feedback Control Theory (Chaps. 1 and 2)

Appendix A: Exercise Problems on Classical Feedback Control Theory (Chaps. 1 and 2) Appendix A: Exercise Problems on Classical Feedback Control Theory (Chaps. 1 and 2) For all calculations in this book, you can use the MathCad software or any other mathematical software that you are familiar

More information

Positioning Servo Design Example

Positioning Servo Design Example Positioning Servo Design Example 1 Goal. The goal in this design example is to design a control system that will be used in a pick-and-place robot to move the link of a robot between two positions. Usually

More information

R10 JNTUWORLD B 1 M 1 K 2 M 2. f(t) Figure 1

R10 JNTUWORLD B 1 M 1 K 2 M 2. f(t) Figure 1 Code No: R06 R0 SET - II B. Tech II Semester Regular Examinations April/May 03 CONTROL SYSTEMS (Com. to EEE, ECE, EIE, ECC, AE) Time: 3 hours Max. Marks: 75 Answer any FIVE Questions All Questions carry

More information

Control System. Contents

Control System. Contents Contents Chapter Topic Page Chapter- Chapter- Chapter-3 Chapter-4 Introduction Transfer Function, Block Diagrams and Signal Flow Graphs Mathematical Modeling Control System 35 Time Response Analysis of

More information

THE 3-DOF helicopter system is a benchmark laboratory

THE 3-DOF helicopter system is a benchmark laboratory Vol:8, No:8, 14 LQR Based PID Controller Design for 3-DOF Helicoter System Santosh Kr. Choudhary International Science Index, Electrical and Information Engineering Vol:8, No:8, 14 waset.org/publication/9999411

More information

Dr Ian R. Manchester

Dr Ian R. Manchester Week Content Notes 1 Introduction 2 Frequency Domain Modelling 3 Transient Performance and the s-plane 4 Block Diagrams 5 Feedback System Characteristics Assign 1 Due 6 Root Locus 7 Root Locus 2 Assign

More information

Charge-Pump Phase-Locked Loops

Charge-Pump Phase-Locked Loops Phase-Locked Loos Charge-Pum Phase-Locked Loos Ching-Yuan Yang National Chung-Hsing University Deartment of Electrical Engineering Concetual oeration of a hase-frequency detector (PFD) PFD 5- Ching-Yuan

More information

06 Feedback Control System Characteristics The role of error signals to characterize feedback control system performance.

06 Feedback Control System Characteristics The role of error signals to characterize feedback control system performance. Chapter 06 Feedback 06 Feedback Control System Characteristics The role of error signals to characterize feedback control system performance. Lesson of the Course Fondamenti di Controlli Automatici of

More information

P-MOS Device and CMOS Inverters

P-MOS Device and CMOS Inverters Lecture 23 P-MOS Device and CMOS Inverters A) P-MOS Device Structure and Oeration B) Relation of Current to t OX, µ V LIMIT C) CMOS Device Equations and Use D) CMOS Inverter V OUT vs. V IN E) CMOS Short

More information

Actual exergy intake to perform the same task

Actual exergy intake to perform the same task CHAPER : PRINCIPLES OF ENERGY CONSERVAION INRODUCION Energy conservation rinciles are based on thermodynamics If we look into the simle and most direct statement of the first law of thermodynamics, we

More information

Systems Analysis and Control

Systems Analysis and Control Systems Analysis and Control Matthew M. Peet Illinois Institute of Technology Lecture : Different Types of Control Overview In this Lecture, you will learn: Limits of Proportional Feedback Performance

More information

Estimation of dynamic behavior and energy efficiency of thrust hybrid bearings with active control

Estimation of dynamic behavior and energy efficiency of thrust hybrid bearings with active control INTERNATIONAL JOURNAL OF MECHANICS Volume 1 18 Estimation of dynamic behavior and energy efficiency of thrust hybrid bearings with active control Alexander Babin Sergey Majorov Leonid Savin Abstract The

More information

Position Control of Induction Motors by Exact Feedback Linearization *

Position Control of Induction Motors by Exact Feedback Linearization * BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 8 No Sofia 008 Position Control of Induction Motors by Exact Feedback Linearization * Kostadin Kostov Stanislav Enev Farhat

More information

ME 304 CONTROL SYSTEMS Spring 2016 MIDTERM EXAMINATION II

ME 304 CONTROL SYSTEMS Spring 2016 MIDTERM EXAMINATION II ME 30 CONTROL SYSTEMS Spring 06 Course Instructors Dr. Tuna Balkan, Dr. Kıvanç Azgın, Dr. Ali Emre Turgut, Dr. Yiğit Yazıcıoğlu MIDTERM EXAMINATION II May, 06 Time Allowed: 00 minutes Closed Notes and

More information

Quanser NI-ELVIS Trainer (QNET) Series: QNET Experiment #02: DC Motor Position Control. DC Motor Control Trainer (DCMCT) Student Manual

Quanser NI-ELVIS Trainer (QNET) Series: QNET Experiment #02: DC Motor Position Control. DC Motor Control Trainer (DCMCT) Student Manual Quanser NI-ELVIS Trainer (QNET) Series: QNET Experiment #02: DC Motor Position Control DC Motor Control Trainer (DCMCT) Student Manual Table of Contents 1 Laboratory Objectives1 2 References1 3 DCMCT Plant

More information

On Line Parameter Estimation of Electric Systems using the Bacterial Foraging Algorithm

On Line Parameter Estimation of Electric Systems using the Bacterial Foraging Algorithm On Line Parameter Estimation of Electric Systems using the Bacterial Foraging Algorithm Gabriel Noriega, José Restreo, Víctor Guzmán, Maribel Giménez and José Aller Universidad Simón Bolívar Valle de Sartenejas,

More information

2.004 Dynamics and Control II Spring 2008

2.004 Dynamics and Control II Spring 2008 MIT OpenCourseWare http://ocw.mit.edu 2.004 Dynamics and Control II Spring 2008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. Massachusetts Institute

More information

OPTIMAL DESIGN AND OPERATION OF HELIUM REFRIGERATION SYSTEMS USING THE GANNI CYCLE

OPTIMAL DESIGN AND OPERATION OF HELIUM REFRIGERATION SYSTEMS USING THE GANNI CYCLE OPTIMAL DESIGN AND OPERATION OF HELIUM REFRIGERATION SYSTEMS USING THE GANNI CYCLE V. Ganni, P. Knudsen Thomas Jefferson National Accelerator Facility (TJNAF) 12000 Jefferson Ave. Newort News, VA 23606

More information

Dr Ian R. Manchester Dr Ian R. Manchester AMME 3500 : Review

Dr Ian R. Manchester Dr Ian R. Manchester AMME 3500 : Review Week Date Content Notes 1 6 Mar Introduction 2 13 Mar Frequency Domain Modelling 3 20 Mar Transient Performance and the s-plane 4 27 Mar Block Diagrams Assign 1 Due 5 3 Apr Feedback System Characteristics

More information

Chapter 1 Fundamentals

Chapter 1 Fundamentals Chater Fundamentals. Overview of Thermodynamics Industrial Revolution brought in large scale automation of many tedious tasks which were earlier being erformed through manual or animal labour. Inventors

More information

Introduction to Control (034040) lecture no. 2

Introduction to Control (034040) lecture no. 2 Introduction to Control (034040) lecture no. 2 Leonid Mirkin Faculty of Mechanical Engineering Technion IIT Setup: Abstract control problem to begin with y P(s) u where P is a plant u is a control signal

More information

Theory of turbomachinery. Chapter 1

Theory of turbomachinery. Chapter 1 Theory of turbomachinery Chater Introduction: Basic Princiles Take your choice of those that can best aid your action. (Shakeseare, Coriolanus) Introduction Definition Turbomachinery describes machines

More information

(a) Torsional spring-mass system. (b) Spring element.

(a) Torsional spring-mass system. (b) Spring element. m v s T s v a (a) T a (b) T a FIGURE 2.1 (a) Torsional spring-mass system. (b) Spring element. by ky Wall friction, b Mass M k y M y r(t) Force r(t) (a) (b) FIGURE 2.2 (a) Spring-mass-damper system. (b)

More information

Time Response Analysis (Part II)

Time Response Analysis (Part II) Time Response Analysis (Part II). A critically damped, continuous-time, second order system, when sampled, will have (in Z domain) (a) A simple pole (b) Double pole on real axis (c) Double pole on imaginary

More information

Feedback Control Systems

Feedback Control Systems ME Homework #0 Feedback Control Systems Last Updated November 06 Text problem 67 (Revised Chapter 6 Homework Problems- attached) 65 Chapter 6 Homework Problems 65 Transient Response of a Second Order Model

More information

Electromagnetic Levitation Control of Contactless Linear Synchronous Drive for Flexible Vertical Transportation

Electromagnetic Levitation Control of Contactless Linear Synchronous Drive for Flexible Vertical Transportation Electromagnetic Levitation Control of Contactless Linear Synchronous Drive for Flexible Vertical Transortation Toshiyuki NAKAI*, Daisuke TATEISHI**, Takafumi KOSEKI*, and Yasuaki AOYAMA*** (*)Deartment

More information

Combining Logistic Regression with Kriging for Mapping the Risk of Occurrence of Unexploded Ordnance (UXO)

Combining Logistic Regression with Kriging for Mapping the Risk of Occurrence of Unexploded Ordnance (UXO) Combining Logistic Regression with Kriging for Maing the Risk of Occurrence of Unexloded Ordnance (UXO) H. Saito (), P. Goovaerts (), S. A. McKenna (2) Environmental and Water Resources Engineering, Deartment

More information

Linear Control Systems Solution to Assignment #1

Linear Control Systems Solution to Assignment #1 Linear Control Systems Solution to Assignment # Instructor: H. Karimi Issued: Mehr 0, 389 Due: Mehr 8, 389 Solution to Exercise. a) Using the superposition property of linear systems we can compute the

More information

Model Design Modeling Approaches

Model Design Modeling Approaches Model Design 1 Peter Fritzson Modeling Aroaches Traditional state sace aroach Traditional signal-style block-oriented aroach Object-oriented aroach based on finished library comonent models Object-oriented

More information

Exam. 135 minutes + 15 minutes reading time

Exam. 135 minutes + 15 minutes reading time Exam January 23, 27 Control Systems I (5-59-L) Prof. Emilio Frazzoli Exam Exam Duration: 35 minutes + 5 minutes reading time Number of Problems: 45 Number of Points: 53 Permitted aids: Important: 4 pages

More information

UNIVERSITY OF WASHINGTON Department of Aeronautics and Astronautics

UNIVERSITY OF WASHINGTON Department of Aeronautics and Astronautics UNIVERSITY OF WASHINGTON Department of Aeronautics and Astronautics Modeling and Control of a Flexishaft System March 19, 2003 Christopher Lum Travis Reisner Amanda Stephens Brian Hass AA/EE-448 Controls

More information

ME scope Application Note 16

ME scope Application Note 16 ME scoe Alication Note 16 Integration & Differentiation of FFs and Mode Shaes NOTE: The stes used in this Alication Note can be dulicated using any Package that includes the VES-36 Advanced Signal Processing

More information

MODEL-BASED MULTIPLE FAULT DETECTION AND ISOLATION FOR NONLINEAR SYSTEMS

MODEL-BASED MULTIPLE FAULT DETECTION AND ISOLATION FOR NONLINEAR SYSTEMS MODEL-BASED MULIPLE FAUL DEECION AND ISOLAION FOR NONLINEAR SYSEMS Ivan Castillo, and homas F. Edgar he University of exas at Austin Austin, X 78712 David Hill Chemstations Houston, X 77009 Abstract A

More information

Alireza Mousavi Brunel University

Alireza Mousavi Brunel University Alireza Mousavi Brunel University 1 » Control Process» Control Systems Design & Analysis 2 Open-Loop Control: Is normally a simple switch on and switch off process, for example a light in a room is switched

More information

Chapter 8. Feedback Controllers. Figure 8.1 Schematic diagram for a stirred-tank blending system.

Chapter 8. Feedback Controllers. Figure 8.1 Schematic diagram for a stirred-tank blending system. Feedback Controllers Figure 8.1 Schematic diagram for a stirred-tank blending system. 1 Basic Control Modes Next we consider the three basic control modes starting with the simplest mode, proportional

More information

Subject: BT6008 Process Measurement and Control. The General Control System

Subject: BT6008 Process Measurement and Control. The General Control System WALJAT COLLEGES OF APPLIED SCIENCES In academic partnership with BIRLA INSTITUTE OF TECHNOLOGY Question Bank Course: Biotechnology Session: 005-006 Subject: BT6008 Process Measurement and Control Semester:

More information

Robust Performance Design of PID Controllers with Inverse Multiplicative Uncertainty

Robust Performance Design of PID Controllers with Inverse Multiplicative Uncertainty American Control Conference on O'Farrell Street San Francisco CA USA June 9 - July Robust Performance Design of PID Controllers with Inverse Multilicative Uncertainty Tooran Emami John M Watkins Senior

More information

University of North Carolina-Charlotte Department of Electrical and Computer Engineering ECGR 4143/5195 Electrical Machinery Fall 2009

University of North Carolina-Charlotte Department of Electrical and Computer Engineering ECGR 4143/5195 Electrical Machinery Fall 2009 University of North Carolina-Charlotte Deartment of Electrical and Comuter Engineering ECG 4143/5195 Electrical Machinery Fall 9 Problem Set 5 Part Due: Friday October 3 Problem 3: Modeling the exerimental

More information

Continuous Steel Casting System Components

Continuous Steel Casting System Components CCC Annual Reort UIUC, August 9, 5 Caturing and Suressing Resonance in Steel Casting Mold Oscillation Systems Oyuna Angatkina Vivek Natarjan Zhelin Chen Deartment of Mechanical Science & Engineering University

More information

Magnetostrictive Dynamic Vibration Absorber (DVA) for Passive and Active Damping

Magnetostrictive Dynamic Vibration Absorber (DVA) for Passive and Active Damping aer : 59 /. Magnetostrictive ynamic Vibration Absorber (VA) for Passive and Active aming C. May a,. uhnen b, P. Pagliarulo b and H. Janocha b a Centre for nnovative Production (ZP), Saarbrücken, ermany,

More information

Process Control & Design

Process Control & Design 458.308 Process Control & Design Lecture 5: Feedback Control System Jong Min Lee Chemical & Biomolecular Engineering Seoul National University 1 / 29 Feedback Control Scheme: The Continuous Blending Process.1

More information

Introduction to Probability and Statistics

Introduction to Probability and Statistics Introduction to Probability and Statistics Chater 8 Ammar M. Sarhan, asarhan@mathstat.dal.ca Deartment of Mathematics and Statistics, Dalhousie University Fall Semester 28 Chater 8 Tests of Hyotheses Based

More information

Tests for Two Proportions in a Stratified Design (Cochran/Mantel-Haenszel Test)

Tests for Two Proportions in a Stratified Design (Cochran/Mantel-Haenszel Test) Chater 225 Tests for Two Proortions in a Stratified Design (Cochran/Mantel-Haenszel Test) Introduction In a stratified design, the subects are selected from two or more strata which are formed from imortant

More information

INC 341 Feedback Control Systems: Lecture 3 Transfer Function of Dynamic Systems II

INC 341 Feedback Control Systems: Lecture 3 Transfer Function of Dynamic Systems II INC 341 Feedback Control Systems: Lecture 3 Transfer Function of Dynamic Systems II Asst. Prof. Dr.-Ing. Sudchai Boonto Department of Control Systems and Instrumentation Engineering King Mongkut s University

More information

which is a convenient way to specify the piston s position. In the simplest case, when φ

which is a convenient way to specify the piston s position. In the simplest case, when φ Abstract The alicability of the comonent-based design aroach to the design of internal combustion engines is demonstrated by develoing a simlified model of such an engine under automatic seed control,

More information

F(p) y + 3y + 2y = δ(t a) y(0) = 0 and y (0) = 0.

F(p) y + 3y + 2y = δ(t a) y(0) = 0 and y (0) = 0. Page 5- Chater 5: Lalace Transforms The Lalace Transform is a useful tool that is used to solve many mathematical and alied roblems. In articular, the Lalace transform is a technique that can be used to

More information

Multivariable PID Control Design For Wastewater Systems

Multivariable PID Control Design For Wastewater Systems Proceedings of the 5th Mediterranean Conference on Control & Automation, July 7-9, 7, Athens - Greece 4- Multivariable PID Control Design For Wastewater Systems N A Wahab, M R Katebi and J Balderud Industrial

More information

FE FORMULATIONS FOR PLASTICITY

FE FORMULATIONS FOR PLASTICITY G These slides are designed based on the book: Finite Elements in Plasticity Theory and Practice, D.R.J. Owen and E. Hinton, 1970, Pineridge Press Ltd., Swansea, UK. 1 Course Content: A INTRODUCTION AND

More information

rate~ If no additional source of holes were present, the excess

rate~ If no additional source of holes were present, the excess DIFFUSION OF CARRIERS Diffusion currents are resent in semiconductor devices which generate a satially non-uniform distribution of carriers. The most imortant examles are the -n junction and the biolar

More information

MODELING THE RELIABILITY OF C4ISR SYSTEMS HARDWARE/SOFTWARE COMPONENTS USING AN IMPROVED MARKOV MODEL

MODELING THE RELIABILITY OF C4ISR SYSTEMS HARDWARE/SOFTWARE COMPONENTS USING AN IMPROVED MARKOV MODEL Technical Sciences and Alied Mathematics MODELING THE RELIABILITY OF CISR SYSTEMS HARDWARE/SOFTWARE COMPONENTS USING AN IMPROVED MARKOV MODEL Cezar VASILESCU Regional Deartment of Defense Resources Management

More information

EE451/551: Digital Control. Relationship Between s and z Planes. The Relationship Between s and z Planes 11/10/2011

EE451/551: Digital Control. Relationship Between s and z Planes. The Relationship Between s and z Planes 11/10/2011 /0/0 EE45/55: Digital Control Chater 6: Digital Control System Design he Relationshi Between s and Planes As noted reviously: s j e e e e r s j where r e and If an analog system has oles at: s n jn a jd

More information

Control Systems. EC / EE / IN. For

Control Systems.   EC / EE / IN. For Control Systems For EC / EE / IN By www.thegateacademy.com Syllabus Syllabus for Control Systems Basic Control System Components; Block Diagrammatic Description, Reduction of Block Diagrams. Open Loop

More information

D(s) G(s) A control system design definition

D(s) G(s) A control system design definition R E Compensation D(s) U Plant G(s) Y Figure 7. A control system design definition x x x 2 x 2 U 2 s s 7 2 Y Figure 7.2 A block diagram representing Eq. (7.) in control form z U 2 s z Y 4 z 2 s z 2 3 Figure

More information

ASPECTS OF POLE PLACEMENT TECHNIQUE IN SYMMETRICAL OPTIMUM METHOD FOR PID CONTROLLER DESIGN

ASPECTS OF POLE PLACEMENT TECHNIQUE IN SYMMETRICAL OPTIMUM METHOD FOR PID CONTROLLER DESIGN ASES OF OLE LAEMEN EHNIQUE IN SYMMERIAL OIMUM MEHOD FOR ID ONROLLER DESIGN Viorel Nicolau *, onstantin Miholca *, Dorel Aiordachioaie *, Emil eanga ** * Deartment of Electronics and elecommunications,

More information

Numerical Linear Algebra

Numerical Linear Algebra Numerical Linear Algebra Numerous alications in statistics, articularly in the fitting of linear models. Notation and conventions: Elements of a matrix A are denoted by a ij, where i indexes the rows and

More information

Filters and Equalizers

Filters and Equalizers Filters and Equalizers By Raymond L. Barrett, Jr., PhD, PE CEO, American Research and Develoment, LLC . Filters and Equalizers Introduction This course will define the notation for roots of olynomial exressions

More information

The Motion Path Study of Measuring Robot Based on Variable Universe Fuzzy Control

The Motion Path Study of Measuring Robot Based on Variable Universe Fuzzy Control MATEC Web of Conferences 95, 8 (27) DOI:.5/ matecconf/27958 ICMME 26 The Motion Path Study of Measuring Robot Based on Variable Universe Fuzzy Control Ma Guoqing, Yu Zhenglin, Cao Guohua, Zhang Ruoyan

More information

VLSI Design Issues. ECE 410, Prof. F. Salem/Prof. A. Mason notes update

VLSI Design Issues. ECE 410, Prof. F. Salem/Prof. A. Mason notes update VLSI Design Issues Scaling/Moore s Law has limits due to the hysics of material. Now L (L=20nm??) affects tx delays (seed), noise, heat (ower consumtion) Scaling increases density of txs and requires more

More information

Characterizing the Behavior of a Probabilistic CMOS Switch Through Analytical Models and Its Verification Through Simulations

Characterizing the Behavior of a Probabilistic CMOS Switch Through Analytical Models and Its Verification Through Simulations Characterizing the Behavior of a Probabilistic CMOS Switch Through Analytical Models and Its Verification Through Simulations PINAR KORKMAZ, BILGE E. S. AKGUL and KRISHNA V. PALEM Georgia Institute of

More information

ME 375 Final Examination Thursday, May 7, 2015 SOLUTION

ME 375 Final Examination Thursday, May 7, 2015 SOLUTION ME 375 Final Examination Thursday, May 7, 2015 SOLUTION POBLEM 1 (25%) negligible mass wheels negligible mass wheels v motor no slip ω r r F D O no slip e in Motor% Cart%with%motor%a,ached% The coupled

More information

Step input, ramp input, parabolic input and impulse input signals. 2. What is the initial slope of a step response of a first order system?

Step input, ramp input, parabolic input and impulse input signals. 2. What is the initial slope of a step response of a first order system? IC6501 CONTROL SYSTEM UNIT-II TIME RESPONSE PART-A 1. What are the standard test signals employed for time domain studies?(or) List the standard test signals used in analysis of control systems? (April

More information

Approximating min-max k-clustering

Approximating min-max k-clustering Aroximating min-max k-clustering Asaf Levin July 24, 2007 Abstract We consider the roblems of set artitioning into k clusters with minimum total cost and minimum of the maximum cost of a cluster. The cost

More information

Controllability and Resiliency Analysis in Heat Exchanger Networks

Controllability and Resiliency Analysis in Heat Exchanger Networks 609 A ublication of CHEMICAL ENGINEERING RANSACIONS VOL. 6, 07 Guest Editors: Petar S Varbanov, Rongxin Su, Hon Loong Lam, Xia Liu, Jiří J Klemeš Coyright 07, AIDIC Servizi S.r.l. ISBN 978-88-95608-5-8;

More information

8.7 Associated and Non-associated Flow Rules

8.7 Associated and Non-associated Flow Rules 8.7 Associated and Non-associated Flow Rules Recall the Levy-Mises flow rule, Eqn. 8.4., d ds (8.7.) The lastic multilier can be determined from the hardening rule. Given the hardening rule one can more

More information

Compressor Surge Control Design Using Linear Matrix Inequality Approach

Compressor Surge Control Design Using Linear Matrix Inequality Approach Comressor Surge Control Design Using Linear Matrix Inequality Aroach Nur Uddin Det. of Electrical Engineering Universitas Pertamina Jakarta, Indonesia Email: nur.uddin@universitasertamina.ac.id Jan Tommy

More information

Prediction of the Excitation Force Based on the Dynamic Analysis for Flexible Model of a Powertrain

Prediction of the Excitation Force Based on the Dynamic Analysis for Flexible Model of a Powertrain Prediction of the Excitation Force Based on the Dynamic Analysis for Flexible Model of a Powertrain Y.S. Kim, S.J. Kim, M.G. Song and S.K. ee Inha University, Mechanical Engineering, 53 Yonghyun Dong,

More information

Bangladesh University of Engineering and Technology. EEE 402: Control System I Laboratory

Bangladesh University of Engineering and Technology. EEE 402: Control System I Laboratory Bangladesh University of Engineering and Technology Electrical and Electronic Engineering Department EEE 402: Control System I Laboratory Experiment No. 4 a) Effect of input waveform, loop gain, and system

More information

Root Locus. Motivation Sketching Root Locus Examples. School of Mechanical Engineering Purdue University. ME375 Root Locus - 1

Root Locus. Motivation Sketching Root Locus Examples. School of Mechanical Engineering Purdue University. ME375 Root Locus - 1 Root Locus Motivation Sketching Root Locus Examples ME375 Root Locus - 1 Servo Table Example DC Motor Position Control The block diagram for position control of the servo table is given by: D 0.09 Position

More information