Comparing filtered PID and smith predictor control of a thermal plant

The paper compares filtered PID control with two filtered Smith predictor modifications and experimentally points out different impact of the derivative terms in the considered controllers on the loop robustness and performance. All structures applied to a thermal plant control are based on its approximation by the first order time-delayed model. They include an nth order binomial filter for measurement noise attenuation. In order to stress the time delay impact, the intrinsic plant time delay is increased by an additional delay in Simulink. The evaluation shows a central role of an appropriate filtration in the controller design. It enables a significant control effort reduction by keeping nearly the same speed of controlled processes. To avoid different tuning scenarios for particular controllers, choice of an optimal solution is based on noise characteristics confronting the speed of transients with the additional control effort required.

[1]  Mikulás Huba Some practical issues in the smith predictor design for FOTD systems , 2017, 2017 4th International Conference on Control, Decision and Information Technologies (CoDIT).

[2]  Eduardo F. Camacho,et al.  Dead-time compensators: A survey , 2008 .

[3]  P.M. Oliveira,et al.  Improving performance/activity ratio for PID controllers , 2005, 2005 International Conference on Control and Automation.

[4]  A. Vitecek,et al.  2DOF PI and PID Controllers Tuning , 2010 .

[5]  S. Skogestad Simple analytic rules for model reduction and PID controller tuning , 2004 .

[6]  Tore Hägglund,et al.  Measurement noise filtering for common PID tuning rules , 2014 .

[7]  Pavol Bistak,et al.  Filtered PI and PID control of an Arduino based thermal plant , 2016 .

[8]  M. Huba,et al.  Laboratory Model of Thermal Plant Identification and Control , 2016 .

[9]  Mikulas Huba Filter choice for an effective measurement noise attenuation in PI and PID controllers , 2015, 2015 IEEE International Conference on Mechatronics (ICM).

[10]  Michel Ruel USING FILTERING TO IMPROVE PERFORMANCE , 2003 .

[11]  Miroslav R. Mataušek,et al.  Optimization of PID controller with higher-order noise filter , 2014 .

[12]  Alf Isaksson,et al.  Derivative filter is an integral part of PID design , 2002 .

[13]  T. Harris,et al.  "Internal model control. 4. PID controller design." Comments , 1987 .

[14]  Eduardo F. Camacho,et al.  Dead-Time Compensators: A Unified Approach , 1998 .

[15]  Eduardo F. Camacho,et al.  Unified approach for robust dead-time compensator design , 2009 .

[16]  O Smith,et al.  CLOSER CONTROL OF LOOPS WITH DEAD TIME , 1957 .

[17]  Julio E. Normey-Rico,et al.  Improving the robustness of dead-time compensating PI controllers , 1997 .

[18]  José Luis Guzmán,et al.  An unified approach for DTC design using interactive tools , 2009 .