Linear Control Systems General Informations. Guillaume Drion Academic year

Transcription

1 Linear Control Systems General Informations Guillaume Drion Academic year

2 SYST General informations Website: Contacts: Guillaume Drion - gdrion@ulg.ac.be Organization: 10 main lessons - Friday 13:30 to 15:30/16:00 10 tutorials - project sessions - Friday 15:30/16:00 to 17:30 (room R3, B28) The course follows the resources provided on the website: Slides and other files will be posted on the main website. 2

3 Goals of the course and evaluation Goals of the course: Lessons: theory and intuition! The main goal of this course is to provide a general (and simple) framework for the design of control systems. Project: to grasp and apply the concepts of the course. Evaluation: Project: oral presentation (groups of 3-4) and final report (groups) NO exam!

4 Schedule of the year 4

5 Linear Control Systems Lecture #1 - Introduction to control systems Guillaume Drion Academic year

6 Systems modeling in three courses SYST0002: Modeling and analysis of systems: open loop. Observing and analyzing the environment Input SYSTEM Output SYST0003: Linear control systems: closed loop. Interacting with the environment Input SYSTEM CONTROLLER Output SYST0017: Advanced topics in systems and control: goes further. (nonlinear systems, chaos, etc.) 6

7 Systems modeling in three courses SYST0002: Modeling and analysis of systems: open loop. Observing and analyzing the environment Input SYSTEM Output SYST0003: Linear control systems: closed loop. Interacting with the environment Input SYSTEM CONTROLLER Output SYST0017: Advanced topics in systems and control: goes further. (nonlinear systems, chaos, etc.) 7

8 The concept of control Alice and Bob went out all night together. The next day (it is 20 C outside): Alice runs a 10km. Bob wakes up really sick. At the end of her run, her body T = 39 C, so she Like Alice, his body T = 39 C, but he feels very warm. wears thin clothes. sweats a lot. wants to take a cold shower. feels very cold. lies underneath several blankets. shivers a lot. wants to take a warm bath. 8

9 The control of body temperature Human body temperature is influenced by the environment and activity. Workout, etc. Open-loop system External T (T E ) + BODY (System) Internal T (T I ) PHYS. RESP. (Actuator) Active if T I T R HYPOTHALAMUS (Sensor) How can we maintain a stable body temperature despite of wide changes in the environment and/or changes in activity level? Reference T (T R ) How does the body senses its own temperature? Why do Alice and Bob feel so different in the same conditions? 9

10 The control of body temperature Human body temperature is influenced by the environment and activity. Workout, etc. Open-loop system External T (T E ) + BODY (System) Internal T (T I ) PHYS. RESP. (Actuator) Active if T I T R HYPOTHALAMUS (Sensor) How can we maintain a stable body temperature despite wide changes in the environment and/or changes in activity level? Reference T (T R ) How does the body senses its own temperature? Why do Alice and Bob feel so different in the same conditions? 10

11 The control of body temperature Human body temperature is influenced by the environment and activity. Workout, etc. Open-loop system External T (T E ) + BODY (System) Internal T (T I ) PHYS. RESP. (Actuator) Active if T I T R HYPOTHALAMUS (Sensor) How can we maintain a stable body temperature despite wide changes in the environment and/or changes in activity level? Reference T (T R ) How does the body sense its own temperature? Why do Alice and Bob feel so different in the same conditions? 11

12 The hypothalamus: a temperature sensor. A part of the brain, called the hypothalamus, contains neurons whose activity is sensitive to changes in temperature. More globally, these neurons represent temperature sensors. Sensors are critical components of a regulatory (control) system. 12

13 The hypothalamus: a temperature sensor. A part of the brain, called the hypothalamus, contains neurons whose activity is sensitive to changes in temperature. More globally, these neurons represent temperature sensors/controllers. Sensors are critical components of a regulatory (control) system. 13

14 The control of body temperature Human body temperature is sensed by the hypothalamus. Workout, etc. Open-loop system External T (T E ) + BODY (System) Internal T (T I ) PHYS. RESP. (Actuator) HYPOTHALAMUS (Sensor) Active if T I T R Reference T (T R ) How can we maintain a stable body temperature despite wide changes in the environment and/or changes in activity level? 14

15 Cold or warm conditions induce a physiological response. If the hypothalamus senses that the temperature is whether too high or too low, it sends a message to induce physiological responses. Cold: vasoconstriction, shivering, curling up, warm clothing, heat source, etc. Warm: vasodilatation, sweating, lethargy, loose clothing, cooling, etc. These physiological responses are actuators. They actively increase or decrease the body temperature. 15

16 The control of body temperature Human body temperature is controlled by the hypothalamus/behavior. External T (T E ) Workout, etc. + BODY (System) Closed-loop system Internal T (T I ) PHYS. RESP. (Actuator) Active if T I T R HYPOTHALAMUS (Sensor) Reference T (T R ) If the body temperature is different than the reference temperature, the hypothalamus induces physiological responses that tend to bring the temperature back to normal. It attempts to correct the error e = T I -T R. 16

17 General structure of a feedback control system (closed-loop) Input + System Output Actuator Controller Sensor Reference The (negative) feedback loop acts against any deviation of the output from the reference value. First role of control: robustness to uncertainty, disturbances, noise, etc. 17

18 Back to Alice and Bob Workout, etc. External T (T E ) + BODY (System) Internal T (T I ) PHYS. RESP. (Actuator) Active if T I T R HYPOTHALAMUS (Sensor) Reference T (T R ) Alice: feels very warm. wears thin clothes. sweats a lot. wants to take a cold shower. 18 Bob: feels very cold. lies underneath several blankets. shivers a lot. wants to take a warm bath.

19 Alice: hyperthermia Workout, etc. External T (T E ) + BODY (System) Internal T (T I ) PHYS. RESP. (Actuator) Active if T I T R HYPOTHALAMUS (Sensor) Reference T (T R ) In the case of Alice, the workout has increased her body temperature. The thalamus sensed it, and induced a physiological response. The controller works great: it tends to reduce the increase in body T induced by the workout. Why is it different for Bob? 19

20 Bob: fever Workout, etc. External T (T E ) + BODY (System) Internal T (T I ) PHYS. RESP. (Actuator) Active if T I T R HYPOTHALAMUS (Sensor) Reference T (T R ) Bob has fever. Fever does not affect the body temperature directly, but increases the reference temperature. Because of the fever, the thalamus thinks Bob s body T is too low. The high body temperature is caused by the controller itself! 20

21 First role of feedback control If the controller senses that the output deviates from it reference value, it acts against this deviation: negative feedback. Control brings robustness to uncertainty, disturbances, etc. to the system. The controller can also have detrimental effects. It has to be carefully designed! Input + System Output Actuator Controller Sensor Reference 21

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23 Example of a feedback system: eye movement. The eye movement is controlled to track a relevant part of the visual field. To track a source, eyes use two types of movements: smooth pursuits and saccades. 23

24 Eye movement: smooth pursuit 24

25 Eye movement: saccades 25

26 What is different between smooth pursuits and saccades? Both smooth pursuits and saccades can bring you to a specific place of the visual field. They both have similar static performance. However, smooth pursuits are slow and precise, whereas saccades are fast and coarse. They differ in their dynamic performance. Second role of control: design of dynamics. 26

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28 Feedforward control: the vestibulo-ocular reflex The vestibular system senses if your head is moving. If it senses movement, it sends a signal to the eye muscles to generate an eye movement equal in amplitude but in the opposite direction. This reflex stabilizes the image on the retina during head movements (ex: reading in a train). This reflex can still occur in comatose patients. 28 This type of control is called feedforward control.

29 Feedback control vs Feedforward control Feedforward control can be used when we can measure the disturbance before it enters the system. Feedforward control can be very efficient, but it requires measure/model of the disturbance outside of the system. 29

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31 Control can create instability: nystagmus In the video, the semicircular canals of the vestibular system are still spinning. They therefore send a signal to the eye muscles to make the eyes turn. On the other hand, the person tries to look at a fixed point in her visual space. The feedback system therefore attempts to counteract the movement generated by the feedforward system, but with a slight delay. This results in instability and oscillations (called nystagmus in this case). 31

32 The importance of a good design! Think about the control of body temperature. It has to be carefully designed: If too slow: the person dies before the temperature is corrected. If too fast: you can have big overshoots, oscillating between periods of coldness and periods of warmness. There is a trade-off between performance and robustness. This course will focus on how to design control systems. 32

33 The concept of control Input + System Output Actuator Controller Sensor Properties: Reference Robustness to uncertainties, disturbances, noise, etc. Design of dynamics: static performance vs dynamic performance. Higher levels of automation. Drawbacks: Can lead to instability. The controller has to be carefully designed! Adds complexity to the system. 33

34 Higher level of automation 34

35 Drones flying in formation Examples of control systems 35

36 Examples of control systems Homeostasis and homeostatic regulation 36

37 SpaceX automatic landing. Examples of control systems

38 Examples of control systems Fly-By-Wire 38

39 Examples of control systems Your phone, when you swipe between screens (sensitivity can be changed by changing the point where the reference changes). 39

40 Examples of control systems Cardiovascular regulation 40

41 Higher level of automation What does a controller look like? 41

42 Control design requires some modeling Reminder: modeling scheme 1. Find an equivalent representation of the system under study 2. Put system into equations (Ordinary Differential Equations or Difference Equations) State-space representation 3. Extract system input/output properties (Laplace/Fourier transform or z-transform) Transfer function System analysis (effects of changes in parameters?) 42

43 Control design requires some modeling Reminder: modeling scheme 1. Find an equivalent representation of the system under study 2. Put system into equations (Ordinary Differential Equations or Difference Equations) State-space representation 3. Extract system input/output properties (Laplace/Fourier transform or z-transform) Transfer function System analysis (effects of changes in parameters?) 43

44 Systems modeling: open-loop A continuous system can be modeled using Ordinary Differential Equations (ODEs). Input SYSTEM Output where is the input vector is the output vector is the state vector (dynamics) States describe the dynamics of the system. Input Output K 44

45 Systems modeling: open-loop A continuous system can be modeled using Ordinary Differential Equations (ODEs). Input SYSTEM Output where is the input vector is the output vector is the state vector (dynamics) In this course, we consider Linear, Time-Invariant (LTI) systems, which can be written where is the dynamics matrix is the input matrix is the output matrix is the feedthrough matrix 45

46 Systems modeling: closed-loop Closing the loop: the controller signal enters in the input Input SYSTEM Output CONTROLLER Classical controller: Proportional-Integral-Derivative (PID) where is an error measure between a reference and the output of the system. 46

47 The classical controller: PID controller PID stands for Proportional-Integral-Derivative. 47

48 The classical controller: PID controller Proportional term: considers the current value of the error. 48

49 The classical controller: PID controller Integral term: considers the past values of the error. 49

50 The classical controller: PID controller Derivative term: predicts the future values of the error. 50

51 PID controller: loop shaping Loop shaping: shaping the loop gains to improve the static and dynamic performances of the controller. 51

52 Control design requires some modeling Reminder: modeling scheme 1. Find an equivalent representation of the system under study 2. Put system into equations (Ordinary Differential Equations or Difference Equations) State-space representation 3. Extract system input/output properties (Laplace/Fourier transform or z-transform) Transfer function System analysis (effects of changes in parameters?) 52

53 The transfer function: open-loop Input/output properties: transfer function (frequency domain via Laplace transform) Idea: describe the system through a simple function that characterizes the way it affects an input U(s) U(s) H(s) Y(s) and s is the complex number frequency (s = σ+jω). If σ=0: Fourier transform! There are different ways to compute the transfer function of a system. However, it is convenient to start from the canonical state-space representation (if available) ẋ = Ax + Bu y = Cx + Du which gives H(s) = Y (s) U(s) = C(sI A) 1 B + D (see next slide) 53

54 The transfer function: closed-loop Input/output properties: transfer function (frequency domain via Laplace transform) Idea: describe the system through a simple function that characterizes the way it affects an input U(s) U(s) H(s) Y(s) C(s) Closed-loop systems are dynamical systems that can be studied with the same tools as open-loop systems. 54

55 Key concepts 1. Open-loop vs closed-loop. 2. Feedback vs feedforward. 3. Static performance vs dynamic performance 4. Stability 5. Performance/Robustness 55