Dead-Time Compensation (纯滞后补偿) Lei Xie Institute of Industrial Control, Zhejiang University, Hangzhou, P. R. China Contents Introduction Smith Predictor for Dead-Time Compensation Improved Smith Predictor Simulation Examples Summary Problem Discussion (1) For the controlled processes, configure your Simulink model & compare their results. (2) Can you provide some compensation approaches for processes with variable & notable dead-time ? D (s) Process R (s) + _ Process Models: Gc(s) Kpgp (s) 2.0 2s G p (s) e ; 4s 1 e s + + 2.0 8s G p ( s) e . 4s 1 Y (s) Conventional PID Control Systems D (s) Process R (s) + _ Process Models: Gc(s) G p (s) Kpgp (s) 2.0 2s e ; 4s 1 e s G p ( s) + + Y (s) 2.0 8s e . 4s 1 Question:Use Ziegler-Nichols or Lambda tuning method to obtain PID parameters and compare their values. Please see the SimuLink model …SISODelayPlant / PIDLoop.mdl Simulation Example #1 Output of Transmitter 78 2.0 2s G p (s) e ; 4s 1 76 74 72 For PID Controller, % Z-N tuning: Kc = 1.2, Ti = 4 min, Td = 1 min 70 68 66 64 Lambda tuning: Kc = 0.83, Ti = 4 min , Td = 1 min 62 setpoint Ziegler-Nichols Tuning Lambda Tuning 60 58 0 20 40 60 80 100 120 Time, min 140 160 180 200 Simulation Example #2 Output of Transmitter 80 2.0 8 s G p (s) e ; 4s 1 78 76 74 For PID Controller, 72 Z-N tuning: Kc = 0.3, Ti = 16 min, Td = 4 min Lambda tuning: % 70 68 66 64 set point Z-N tuning Lambda tuning, Td = 1 min Lambda tuning, Td = 4 min 62 Kc = 0.2, Ti = 4 min , Td = 1 min 60 58 0 20 40 60 80 100 120 Time, min 140 160 180 200 Smith’s Idea (1957) D (s) R (s) + _ Process + Gc(s) + e s Kpgp (s) Y (s) D (s) + R (s) + _ Gc(s) + Process Kpgp (s) e s Y (s) Basic Smith Predictor D (s) R (s) + _ U(s) Gc(s) Process + + Kpgp (s) + + m s _ + Y 1(s) e s e Km gm (s) Y (s) Y 2(s) Smith Predictor Smith Predictor #2 D (s) U (s) R (s) Gc(s) + _ + K m g m (s ) + + K p g p ( s )e Y (s) p s K m g m ( s )e m s _ + + Please see the SimuLink model …SISODelayPlant / PID_Smith.mdl Results of Basic Smith Predictor with an Accurate Model Output of Transmitter 80 Gm ( s) G p ( s) 78 2.0 8 s e ; 4s 1 76 74 72 Simple PID: % 70 Kc = 0.2, Ti = 4 min , Td = 1 min 68 66 64 PID + Smith: Kc = 2, Ti = 4 min , Td = 1 min set point PID with Smith compensator Simple PID 62 60 58 0 20 40 60 80 100 120 Time, min 140 160 180 200 Results of Basic Smith Predictor with an Inaccurate Model Output of Transmitter 2.0 8 s Gm ( s ) e ; 4s 1 2.0 6 s G p (s) e 4s 1 85 80 75 % Simple PID: Kc = 0.2, Ti = 4 min , Td = 1 min PID + Smith: Kc = 2, Ti = 4 min , Td = 1 min 70 65 set point PID + Smith Simple PID 60 55 0 20 40 60 80 100 120 Time, min 140 160 180 200 Improved Smith Predictor D (s) R (s) U (s) Gc(s) + _ + + + K p g p ( s )e K m g m ( s )e m s K m g m (s ) Y (s) p s _ + + Gf(s) 1 Prediction Error Filter:G f (s) Tf s 1 Results of Improved Smith Predictor with an Inaccurate Model Output of Transmitter 80 2.0 8 s e ; 4s 1 2.0 6 s G p (s) e ; 4s 1 1 G f (s) 4s 1 Gm ( s ) 78 76 74 72 % 70 68 66 PID + Smith: Kc = 2, Ti = 4 min , Td = 1 min 64 set point PID + Smith with Gm =Gp PID + Smith with Gm <> Gp Simple PID 62 60 58 0 20 40 60 80 100 120 Time, min 140 160 180 200 Summary The principle of Smith predictor for deadtime compensation Improved Smith predictor for a controlled process with an inaccurate model Comparison of the Simple PID and the PID with a Smith predictor Next Topic: Coupling of Multivariable Systems and Decoupling Concept of Relative Gains Calculation of Relative Gain Matrix Rule of CVs and MVs Pairing Linear Decoupler from Block Diagrams Nonlinear Decoupler from Basic Principles Application Examples Problem Discussion for Next Topic For the two-input-two-input controlled system, design your control schemes. Suppose that F1SP F1m FC 01 F2SP F2m FC 02 FT 01 C1 F1 C2 F2 F F1 F2 , C ; F1 F2 FT 02 F1, C1 Fm 0.5 C Am 1 e 5 s , , ; F s 1 C 4s 1 C 2s 1 Initial states: F10 75, F20 25, C1 60%, C2 40%. F2, C2 u2 u1 ASP AC 11 FC 03 Am FSP Fm AT 11 FT 03 C F