Design of GPC closed-loop performances using multi-objective optimisation

In this paper, a strategy for automatic tuning of predictive controller synthesis parameters based on multi-objective optimisation is proposed. This strategy allows computation of the predictive controller synthesis parameters (the prediction horizon, the control horizon and the cost weighting factor) by minimising a set of closed-loop performances (the overshoot, the variance of the control and the settling time). Two simulation examples are presented to illustrate the performance of this strategy in the adjustment of generalised predictive control parameters.

[1]  David W. Clarke,et al.  Generalized Predictive Control - Part II Extensions and interpretations , 1987, Autom..

[2]  Alberto Bemporad,et al.  Multiobjective model predictive control , 2009, Autom..

[3]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[4]  Weidong Wen,et al.  Multi-objective optimisation of steel frame of solid garage based on genetic algorithm , 2010, Int. J. Model. Identif. Control..

[5]  A. Farag,et al.  Tuning of a PID controller Using a Multi-objective Optimization Technique Applied to A Neutralization Plant , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[6]  M. Ksouri,et al.  Constrained Nonlinear Multi-objective Predictive Control , 2006, The Proceedings of the Multiconference on "Computational Engineering in Systems Applications".

[7]  Xavier Blasco,et al.  Generalized predictive control using genetic algorithms (GAGPC) , 1998 .

[8]  Zheng Li,et al.  Predictive controller design for multivariable process system based on support vector machine model , 2011, Int. J. Model. Identif. Control..

[9]  Adrian Gambier,et al.  Multi-objective Optimal Control: An Overview , 2007, 2007 IEEE International Conference on Control Applications.

[10]  T. Sato,et al.  Design of a GPC-based PID controller for controlling a weigh feeder , 2010 .

[11]  Gary B. Lamont,et al.  Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art , 2000, Evolutionary Computation.

[12]  Joo-Shin Park,et al.  Pareto optimisation of grillage system with multi-objectives , 2009, Int. J. Model. Identif. Control..

[13]  Mekki Ksouri,et al.  Application of Fuzzy Logic to the On-Line Adjustment of the Parameters of a Generalized Predictive Controller , 1998, Intell. Autom. Soft Comput..

[14]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[15]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[16]  A. Berro,et al.  Optimisation multiobjectif et stratégies d' évolution en environnement dynamique , 2001 .

[17]  A. Gambier,et al.  MPC and PID control based on Multi-Objective Optimization , 2008, 2008 American Control Conference.

[18]  Mayuresh V. Kothare,et al.  Simultaneous linear and anti-windup controller synthesis using multiobjective convex optimization , 2009, Autom..

[19]  Zhenyu Yang,et al.  Automatic tuning of PID controller for a 1-D levitation system using a genetic algorithm - a real case study , 2006, 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control.

[20]  Gary B. Lamont,et al.  Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.