Multi-objective robust PID controller tuning using multi-objective differential evolution

PID controller has been widely applied in engineering area. In this paper, multi-objective differential evolution (MODE) is used to design a multi-objective robust PID controller for two MEMO systems known as distillation column plant and longitudinal control system of the super maneuverable F18/HARV fighter aircraft. Multi-objective robust PID controller problem is formulated by minimizing integral squared error (ISE) and balanced robust performance criteria. The performance of the optimum PID controllers that obtain by MODE is compared with performance reported in literature by other methods in terms of the sum of ISE and balanced robust performance criteria. The results show that the PID controllers obtained by MODE can outperform various optimal PID controllers reported in literature.

[1]  Peter J. Fleming,et al.  Multiobjective gas turbine engine controller design using genetic algorithms , 1996, IEEE Trans. Ind. Electron..

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

[3]  Marco Laumanns,et al.  An efficient, adaptive parameter variation scheme for metaheuristics based on the epsilon-constraint method , 2006, Eur. J. Oper. Res..

[4]  H. Zhong-xi,et al.  Multi-objective Optimization with Modified Pareto Differential Evolution , 2008, 2008 International Conference on Intelligent Computation Technology and Automation (ICICTA).

[5]  Ponnuthurai N. Suganthan,et al.  Multi-objective differential evolution with diversity enhancement , 2010, Journal of Zhejiang University SCIENCE C.

[6]  Alberto Herreros,et al.  Design of PID-type controllers using multiobjective genetic algorithms. , 2002, ISA transactions.

[7]  Shinn-Ying Ho,et al.  Designing structure-specified mixed H/sub 2//H/sub /spl infin// optimal controllers using an intelligent genetic algorithm IGA , 2005, IEEE Transactions on Control Systems Technology.

[8]  Shinn-Ying Ho,et al.  OSA: orthogonal simulated annealing algorithm and its application to designing mixed H2/H∞ optimal controllers , 2004, IEEE Trans. Syst. Man Cybern. Part A.

[9]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[10]  Ponnuthurai N. Suganthan,et al.  Multi-objective optimization using self-adaptive differential evolution algorithm , 2009, 2009 IEEE Congress on Evolutionary Computation.

[11]  Hassan Bevrani,et al.  Multiobjective PI/PID Control Design Using an Iterative Linear Matrix Inequalities Algorithm , 2007 .

[12]  W. Marsden I and J , 2012 .

[13]  Shiow-Fen Hwang,et al.  A Novel Intelligent Multiobjective Simulated Annealing Algorithm for Designing Robust PID Controllers , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[14]  Bruce A. Francis,et al.  Feedback Control Theory , 1992 .

[15]  H. Marquez,et al.  Robust Controller Design And Pid Tuning For Multivariable Processes , 2002 .

[16]  J. Doyle,et al.  Robust and optimal control , 1995, Proceedings of 35th IEEE Conference on Decision and Control.