Summary
In this paper, a novel design method for robust controllers based on Cooperative Particle Swarm Optimization (PSO) is proposed. The design is formulated as a constrained optimization problem, i.e., the minimization of a nominal H 2 performance index subject to a H ∞ robust stability constraint. The method focuses on two (PSOs): One for minimizing the performance index, and the other for maximizing the robust stability constraint. Simulation results are given to illustrate the effectiveness and validity of the approach.
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References
Bernstein, B.S. and Haddad, W.M. (1994) LQG Control with a Performance Bound: A Riccati Equation Approach. IEEE Trans. Automatic Control 34 (3), pp. 293–305
Doyle, J.C., Zhou, K., Glover, K., and Boddenheimer, B. (1994) Mixed and Performance Objectives II: Optimal Control. IEEE Trans. Automatic Control 39 (8), pp. 1575–1587
Snaizer, M. (1994) An Exact Solution to General SISO Mixed Problems via Convex Optimization. IEEE Trans. Automatic Control 39 (12), pp. 2511–2517
Chen, B.-S., Cheng, Y.-M., and Lee, C.-H. (1995) A Genetic Approach to Mixed Optimal PID Control IEEE Control Systems Magazine, pp. 51–60
Lo Bianco, C.G., and Piazzi, A. (1997) Mixed Fixed-Structure Control via Semi-Infinite Optimization. In Proc. of the 7th IFAC International Symposium on CACSD, Gent, Belgium, pp. 329–334
Krohling, R.A. (1998) Genetic Algorithms for Synthesis of Mixed Fixed-Structure Controller. In Proc. of the 13th IEEE International Symposium on Intelligent Control, ISIC’98, Gaithersburg, USA, pp. 30–35
Krohling, R.A., Coelho, L.S., and Coelho, A.A.R. (1999) Evolution Strategies for Synthesis of Mixed Fixed-Structure Controllers. In Proceedings of the IFAC World Congress, Beijing, China, pp. 471–476
Doyle, J.C. Francis, B.A., and Tannenbaum, A. R. (1992) Feedback Control Theory. Macmillan Publishing, New York, USA
Newton, G.C., Gould, L.A., and Kaiser, J.F. (1957) Analytic Design of Linear Feedback Controls. John Wiley & Sons, New York
Jury, E.I. (1974) Inners and the Stability of Dynamic Systems. John Wiley, New York
Eberhart, R.C., and Kennedy, J. (1995) A New Optimizer Using Particle Swarm Theory. In Proc. of the 6th. Int. Symposium on Micro Machine and Human Science, Nagoya, Japan. IEEE Service Center, Piscataway, NJ, pp. 39–43
Kennedy, J., and Eberhart, R.C. (1995) Particle swarm optimization. In Proc. of the IEEE Int. Conf. on Neural Networks IV, IEEE Service Center, Piscataway, NJ, pp. 1942–1948
Shi, Y., and Eberhart, R.C. (1998) Parameter Selection in Particle Swarm Optimization. In Proc. of the Conf. on Evolutionary Programming VII: EP98, Springer-Verlag, New York, pp. 591–600
Shi, Y. and Eberhart, R.C. (1998) A Modified Particle Swarm Optimizer. In Proc. of the IEEE International Conference on Evolutionary Computation, Piscataway, IEEE Service Center, NJ, pp. 69–73
Fan, H.-Y., and Shi, Y. (2001) Study of Vmax of the Particle Swarm Optimization Algorithm. In Proc. of the Workshop on Particle Swarm Optimization. Purdue School of Engineering and Technology, IUPUI, Indianapolis,IN
Potter, M. A. and De Jong, K. (1994) A Cooperative Coevolutionary Approach to Function Optimization. In Proc. of the 3rd Conference on Parallel Problem Solving from Nature. Springer-Verlag, New York, pp. 257
Potter, M. A. (1997) The Design and Analysis of a Computational Model of Cooperative Coevolution. Doctoral dissertation, George Mason University, 1997
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Krohling, R.A., dos Coelho, L.S., Shi, Y. (2003). Cooperative Particle Swarm Optimization for Robust Control System Design. In: Benítez, J.M., Cordón, O., Hoffmann, F., Roy, R. (eds) Advances in Soft Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3744-3_30
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DOI: https://doi.org/10.1007/978-1-4471-3744-3_30
Publisher Name: Springer, London
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