Multiobjective tuning of PI controller using the NNC Method: Simplified problem definition and guidelines for decision making

This paper presents the application of the NNC method to the tuning of PI controllers. The main contribution is on the analysis of the tradeoff among different performance indexes as well as the need of considering the robustness as another tradeoff. Robustness has been included during last year's. However, the authors do question if it is needed to include an explicit robustness measure or is better to find its correlation with another performance-like figure of merit. The use of specific compromise criteria to select an unique solution from the Pareto front generates a possibility for tuning a PI control that generates better system outputs than existing tuning methods.

[1]  Kay Chen Tan,et al.  Advances in Evolutionary Multi-objective Optimization , 2012, SOFA.

[2]  K.J. ÅSTRÖM,et al.  Design of PI Controllers based on Non-Convex Optimization , 1998, Autom..

[3]  Tore Hägglund,et al.  Benchmark systems for PID control , 2000 .

[4]  Sigurd Skogestad,et al.  Simple analytic rules for model reduction and PID controller tuning , 2003 .

[5]  Kaisa Miettinen,et al.  Nonlinear multiobjective optimization , 1998, International series in operations research and management science.

[6]  Michael W. Foley,et al.  Comparison of PI controller tuning methods , 2005 .

[7]  S. Hart,et al.  Handbook of Game Theory with Economic Applications , 1992 .

[8]  Tore Hägglund,et al.  Criteria and Trade-offs in PID Design , 2012 .

[9]  K. Åström,et al.  Revisiting The Ziegler‐Nichols Tuning Rules For Pi Control , 2002 .

[10]  Piero P. Bonissone,et al.  Multicriteria decision making (mcdm): a framework for research and applications , 2009, IEEE Computational Intelligence Magazine.

[11]  Ramon Vilanova,et al.  Model-reference robust tuning of 2DoF PI controllers for first- and second-order plus dead-time controlled processes , 2012 .

[12]  A. Messac,et al.  The normalized normal constraint method for generating the Pareto frontier , 2003 .

[13]  Christopher A. Mattson,et al.  Pareto Frontier Based Concept Selection Under Uncertainty, with Visualization , 2005 .

[14]  Karl Johan Åström,et al.  PID Controllers: Theory, Design, and Tuning , 1995 .

[15]  Xavier Blasco Ferragud,et al.  Multiobjective controller design handling human preferences , 2006, Eng. Appl. Artif. Intell..

[16]  Bengt Lennartson,et al.  Evaluation and simple tuning of PID controllers with high-frequency robustness , 2006 .