Chapter3 control system characteristics solution.pptx

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1. Chapter 3 TUNING OF CONTROLLERS Muhammad Usman Mukhtiar

2. CONTENTS:- INTRODUCTION PID CONTROLLER TUNNING PROCESS DIFFERENT TUNING METHODS ZIEGLER-NICOLAS TUNNING METHOD CONCLUSION

3. INTRODUCTION:- The Controller : It decides the control variable in order to bring the process variable as close as to the set point . PID controller: It continuously calculates an error value e(t) as the difference between a desired set point and a measured process variable and applies a correction based on proportional ,integral and derivative terms which give their to controller types.

4. PID Controller:- Proportional Term(P): It is a constant directly related to the amount of the error. If you have large error ,the term gives you a large output, and if you have a small error, it will give you a small output. In simple term affects the speed to reach your target. Integral Term(I): It is constant related to integration(summation) of errors over time. If your error is increasing, this term gives you a large output. However if the error is decreasing, the I term give you a small output. Thus it is used to fine tune your results i.e. when you almost reach your goal, the P term can not serve you any more. Derivative Term(D): It is constant related to the rate of change of errors with time. i.e you have a highly dynamic systems like a multi- coptor , the D-term will give you higher output to catch up with the changes.

5. NEED OF PID CONTROLLER :- PARAMETER RISE TIME OVERSHOOT SETTLING TIME STEADY-STATE ERROR STABILITY K p Decrease Increase Small Change Decrease Degrade K i Decrease Increase Increase Eliminate Degrade K d Minor Change Decrease Decrease No Effect Improve if Kd Small

6. PID CONTROLLER parametrs :

7. TUNING PROCEDURES OF PID CONTROLLER :- After nulling all the parameters ,increase the P term so that the output reaches the target in shortest possible time. If your output starts oscillating ,it means you have too much P. lower your P term until the oscillation disappears. You will end up slightly higher or lower than your target. Now increase I term slightly until your errors goes away. Note that usual I values are very small and they are dependent on the update rate of your PID loop. If you feel your output is oscillating lower your I term. Now for highly dynamic system we need to adjust the D term also. If your system starts oscillating with high frequency and small transition it means we have too much D term which is amplifying the noise. If it has too much noise its better to keep the D parameter to zero. At last watch your limits . If you are changing the previous parameters without any noticeable change in the output This Completes the tuning procedure of the PID Controller.

8. TUNNING OF PID CONTROLLER:-

9. TUNNING PROCESSES :- METHODS ADVANTAGES DISADVANTAGES Manual Tuning No Math Required, Online Requires Experienced Personnel Ziegler-Nichols Proven Method, Online Process Upset, Some Trial –and- Error, Very Aggressive Tuning Cohen-Coon Good Process Models Some Math; Offline; Only good for First-Order Process Software Tools Consistent Tuning; Online or Offline Some Cost Or Training Involved

10. ZIEGLER-NICHOLUS METHOD ( Open loop Method ):- It is done in manual mode. It is way of relating the process parameters( i.e Controller gain & Reset time). It has been developed for use on delay-followed by first-order-lag-processes. Once the value of process parameters are obtained the PID parameters can be calculated from the below table.

11. Process parameter(Delay time, Process gain PROCESS REACTION CURVE - SIMPLE

12. ZIEGLER-NICHOLUS METHOD ( Close loop Method ):-continue In controller automatic mode(operating condition), PV approximate to set point, change the %PB of controller to maximum, Integral time maximum and Derivative time minimum, then decrease %PB and take load step(change set-point or process loads) for monitor PV responding until PV occur slight oscillation. Record %PB of Oscillate condition(Ultimate controller gain , Kcu ) and Band width( ultimate period , Pu ).

13. ZIEGLER-NICHOLUS METHOD ( close loop Method ):-continue Then we roughly tune the initial value as the below table; Where Kc = Controller gain %PB= 1/ Kc x 100(%) %PB=% Proportional Band Ti= Integral Time or Reset time (Sec./Repeat) Td= Derivative time or rate (Sec.)

14. CONCLUSION:- P Controller mitigates error but initiates offset. I Controller mitigates offset but initiates overshoot. D Controller mitigates overshoot for optimization.

15. Settling Time

16. Peak Overshoot

17. Rise Time

18. Example(Important)

19. Steady State Error

20. Example for Steady state error

21. Steady State Error for Non-Unity Feedback Systems

22. Summary To summarise : P: Proportional  controller to reduce the transient period. Changes the magnitude only. I: Integral  controller to reduce the time invariant error Lags the output phase. D: Derivative  controller to minimize the transient errors like overshoot, oscillatory response. Leads the output phase. PI: Reduces rise time and steady state errors. Changes the magnitude as well as lags the output. PD: Reduces rise time and transient errors such as overshoot, oscillations in output. Changes both the magnitude as well as adds a leading phase to the output. PID: General case of a controller. Can be used to control the magnitude and lead/ lag phase problems. Changes the magnitude and can add positive or negative phase to the output as per the requirements.

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