Optimized Retuning of PID Controllers for TITO Processses

Abstract In this paper we propose a methodology to evaluate the performance of decentralized PID controllers for two-inputs-two-outputs processes and to retune the parameters. In particular, the model of the process is estimated based on a technique that exploits the final value theorem. Then, an evolutionary algorithm is applied in order to find the Pareto front by considering a multiobjective optimization problem. Finally, the performance obtained with the current tuning is compared with the optimal ones and, in case it is necessary, the PID parameters are retuned accordingly. A procedure to achieve the Nash optimal point is also proposed.

[1]  Somanath Majhi,et al.  Obtaining controller parameters for a new Smith predictor using autotuning , 2000, Autom..

[2]  William L. Luyben,et al.  Simple method for tuning SISO controllers in multivariable systems , 1986 .

[3]  Julio E. Normey-Rico,et al.  Implementation and test of a new autotuning method for PID controllers of TITO processes , 2017 .

[4]  Biao Huang,et al.  Performance Assessment of Control Loops , 1999 .

[5]  Antonio Visioli,et al.  Simultaneous closed-loop automatic tuning method for cascade controllers , 2011 .

[6]  Tore Hägglund.  Industrial implementation of on-line performance monitoring tools , 2005 .

[7]  Stephen P. Boyd,et al.  MIMO PID tuning via iterated LMI restriction , 2016 .

[8]  Moonyong Lee,et al.  Analytical Design of Multiloop PID Controllers for Desired Closed-Loop Responses (R&D Note) , 2004 .

[9]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[10]  Julio E. Normey-Rico,et al.  An automatic tuning methodology for a unified dead-time compensator , 2014 .

[11]  Antonio Visioli,et al.  An industrial application of a performance assessment and retuning technique for PI controllers. , 2010, ISA transactions.

[12]  Antonio Visioli,et al.  Optimal Nash tuning rules for robust PID controllers , 2017, J. Frankl. Inst..

[13]  Antonio Visioli,et al.  Automatic Tuning of Feedforward Controllers for Disturbance Rejection , 2014 .

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

[15]  Mohieddine Jelali,et al.  An overview of control performance assessment technology and industrial applications , 2006 .

[16]  Antonio Visioli,et al.  Performance Assessment and Retuning of PID Controllers , 2009 .

[17]  S. G. Tzafestas,et al.  Controller tuning with evolutionary multiobjective optimization , 2017 .

[18]  Dorothea Heiss-Czedik,et al.  An Introduction to Genetic Algorithms. , 1997, Artificial Life.

[19]  R. K. Wood,et al.  Terminal composition control of a binary distillation column , 1973 .

[20]  Mohieddine Jelali,et al.  The current state of control loop performance monitoring – A survey of application in industry , 2016 .

[21]  Antonio Visioli,et al.  Performance assessment and retuning of PID controllers for load disturbance rejection , 2012 .

[22]  Salim Ahmed,et al.  A sequential optimization procedure to tune MIMO PID controllers , 2017, 2017 Indian Control Conference (ICC).

[23]  Tore Hägglund,et al.  Software-based optimal PID design with robustness and noise sensitivity constraints , 2015 .

[24]  S. Joe Qin,et al.  Control performance monitoring — a review and assessment , 1998 .

[25]  Antonio Visioli,et al.  Performance assessment and retuning of PID controllers for integral processes , 2010 .