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http://dx.doi.org/10.5391/JKIIS.2006.16.5.562

Model Predictive Control System Design with Real Number Coding Genetic Algorithm  

Bang, Hyun-Jin (중앙대학교 전자전기공학부)
Park, Jong-Chon (중앙대학교 전자전기공학부)
Hong, Jin-Man (중앙대학교 전자전기공학부)
Lee, Hong-Gi (중앙대학교 전자전기공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.16, no.5, 2006 , pp. 562-567 More about this Journal
Abstract
Model Predictive Control(MPC) system uses the current input which minimizes the difference between the desired output and the estimated output in the receding horizon scheme. In many cases (for example, system with constraints or nonlinear system), however, it is not easy to find the optimal solution to the above problem. In this paper, we show that real number coding genetic algorithm can be used to solve the optimal problem for MPC effectively. Also, we show by simulation that the real coding algorithm is mote natural and advantageous than the digital coding one.
Keywords
genetic algorithm; real number coding; predictive control; receding horizon control;
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1 강훈, 심귀보, '지능정보시스템', 브레인코리아, 2003
2 진강규, '유전알고리즘과 그 응용', 교우사, 2000
3 E.F. Camacho and C. Bordons, 'Model Predictive Control', Springer, 2004
4 J.A. Rossiter, 'Model-Based Predictive Control', CRC Press, 2003
5 S.C. Shin and Z. Bien, 'Constrained GA-based Predictive Control,' 대한전자공학회, 추계종합학술대회논문집, 22권 2호, pp.732-735, 1999   과학기술학회마을
6 S.C. Shin and S.B. Park, 'GA-based predictive control for nonlinear processes', Electronics Letters, Vol.34. pp.1980-1981, 1998   DOI   ScienceOn