Lecture 7: Anti-windup and friction compensation

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1 Lecture 7: Anti-windup and friction compensation Compensation for saturations (anti-windup) Friction models Friction compensation Material Lecture slides

2 Course Outline Lecture 1-3 Lecture 2-6 Lecture 7-8 Lecture 9-13 Lecture 14 Modelling and basic phenomena (linearization, phase plane, limit cycles) Analysis methods (Lyapunov, circle criterion, describing functions) Common nonlinearities (Saturation, friction, backlash, quantization) Design methods (Lyapunov methods, Backstepping, Optimal control) Summary

3 Last lecture: Stable periodic solution r e u y G(s) G(iω) 1/N(A) G(s)= (s+10)2 (s+1) 3 with feedback u= sgny gives one stable and one unstable limit cycle. The left most intersection corresponds to the stable one.

4 Periodic Solutions in Relay System The relay gainn(a) is higher for smalla: Big amplitudes Small relay gain No encirclement Shrinking amplitudes Growing relay gain One encirclement Growing amplitudes Shrinking relay gain Small amplitudes High relay gain No encirclement Shrinking amplitudes Growing relay gain Stable periodic orbit Unstable periodic orbit

5 Today s Goal To be able to design and analyze antiwindup schemes for PID state-space systems and Kalman filters (observers) To understand common models of friction To design and analyze friction compensation schemes

6 Windup The Problem v u G(s) C(s) The feedback path is broken when u saturates The controller C(s) is a dynamic system Problems when controller is unstable (or stable but not AS) Example: I-part in PID-controller

7 Example-Windup in PID Controller 2 1 Output Input Time Dashed line: ordinary PID-controller Solid line: PID-controller with anti-windup

8 Anti-windup for PID-Controller ( Tracking ) Anti-windup (a) with actuator output available and (b) without (a) y KT d s Actuator e K v u K T i 1 s + 1 e s T t )b( y KT d s Actuatormodel Actuator e K v u K T i 1 s + 1 e s T t

9 Choice of Tracking TimeT t y set-point T t =3 T t =2 T t =0.1,T t =1 T t =0.1 T t =1 T t =3 T t =2 With very smallt t (large gain1/t t ), spurious errors can saturate the output, which leads to accidental reset of the integrator. Too larget t gives too slow reaction (little effect). The tracking timet t is the design parameter of the anti-windup. Common choices:t t =T i ort t = T i T d.

10 State feedback with Observer x m y Observer State feedback Actuator x ˆ Σ L sat(v) ˆx = Aˆx+Bsat(v)+K(y Cˆx) v = L(x m ˆx) ˆx is estimate of process state,x m desired (model) state. Need model of saturation if sat(v) is not measurable

11 Antiwindup General State-Space Controller State-space controller: ẋ c (t) = Fx c (t)+gy(t) u(t) = Cx c (t)+dy(t) Windup possible if F is unstable and u saturates. (a) y S A u (b) y S B u Idea: Rewrite representation of control law from (a) to (b) such that: (a) and (b) have same input-output relation (b) behaves better when feedback loop is broken, ifs B stable

12 Antiwindup General State-Space Controller Mimic the observer-based controller: ẋ c = Fx c +Gy+K(u Cx c Dy) }{{} =0 = (F KC)x c +(G KD)y+Ku = F 0 x c +G 0 y+ku Design so thatf 0 =F KC has desired stable eigenvalues Then use controller ẋ c = F 0 x c +G 0 y+ku u = sat(cx c +Dy)

13 State-space controller without and with anti-windup: D F y G s 1 x c C u D F KC y G KD s 1 x c C v sat u K

14 5 Minute Exercise How would you do antiwindup for the following state-feedback controller with observer and integral action? y ref 1 s L i u Process y L x Estimator

15 Saturation Optimal control theory (later) Multi-loop Anti-windup (Cascaded systems): Difficult problem, several suggested solutions Turn off integrator in outer loop when inner loop saturates

16 Friction Present almost everywhere Often bad Friction in valves and mechanical constructions Sometimes good Friction in brakes Sometimes too small Earthquakes Problems How to model friction How to compensate for friction

17 Stick-slip Motion k(y x) F x y Time Time Time

18 DIP Position Control of Servo with Friction Hunting F Friction x r u Σ 1 ms v 1 s x Time Time Time

19 3 Minute Exercise What are the signals in the previous plots? What model of friction has been used in the simulation?

20 Friction N N F F F

21 Lubrication Regimes Friction Sticking Boundary lubrication Mixed lubrication Full fluid lubrication Velocity Hard to get good model atv=0

22 Stribeck Effect For low velocity: friction increases with decreasing velocity Stribeck (1902) Steady state friction: Joint Friction [Nm] Velocity [rad/sec]

23 Frictional Lag Dynamics are important also outside sticking regime Hess and Soom (1990) Experiment with unidirectional motionv(t)=v 0 +asin(ωt) Hysteresis effect! Friction Velocity

24 Classical Friction Models a) b) F F v v c) d) F F v v c) F(t) = { Fc signv(t)+f v v(t) v(t) =0 max(min(f e (t),f s ), F s ) v(t)=0 F e (t)= external applied force,f c,f v,f s constants

25 Advanced Friction Models See PhD-thesis by Henrik Olsson Karnopp model Armstrong s seven parameter model Dahl model Bristle model Reset integrator model Bliman and Sorine Wit-Olsson-Åström

26 Demands on a model To be useful for control the model should be sufficiently accurate, suitable for simulation, simple, few parameters to determine. physical interpretations, insight Pick the simplest model that does the job! If no stiction occurs the v = 0-models are not needed.

27 Friction Compensation Lubrication Integral action (beware!) Dither Non-model based control Model based friction compensation Adaptive friction compensation

28 Integral Action The integral action compensates for any external disturbance Good if friction force changes slowly (v constant). To get fast action when friction changes one must use much integral action (smallt i ) Gives phase lag, may cause stability problems etc

29 Deadzone - Modified Integral Action Modify integral part toi= K t T 0ê(t)dτ i e(t) η e(t)> η where input to integrator ê = 0 e(t) < η e(t)+ η e(t)< η ê(t) η e(t) Advantage: Avoid that small static error introduces limit cycle Disadvantage: Must accept small error (will not go to zero)

30 Mechanical Vibrator Dither Avoids sticking atv=0where there usually is high friction by adding high-frequency mechanical vibration (dither ) x r + F Friction + + PID 1 u ms v 1 s x Cf., mechanical maze puzzle (labyrintspel)

31 Adaptive Friction Compensation Coulomb Friction F = a sgn(v) F friction Friction u PID ms v 1 s x F friction Friction estimator Assumption: v measurable. Friction estimator: F friction ż = ku PID sgn(v) â = z km v = âsgn(v)

32 Result:e=a â 0ast, since de dt = dâ dt = dz dt +kmd dt v = ku PID sgn(v)+km vsgn(v) = ksgn(v)(u PID m v) = ksgn(v)(f ˆF) = k(a â) = ke Remark: Careful with d dt v atv=0.

33 The Knocker Combines Coulomb compensation and square wave dither Tore Hägglund, Innovation Cup winner + patent 1997

34 Example Friction Compensation Velocity control with a) P-controller b) PI-controller c) P + Coulomb estimation

35 Results 1 P-controller 1 PI-controller v v ref u P-controller with Coulomb estimation

36 Next Lecture Backlash Quantization

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