Design of optimal fuzzy controllers for stabilization of a Helicopter Simulator using hybrid Elite Genetic Algorithm and Tabu Search

In this paper, a new intelligent method based on hybridization of Elite Genetic Algorithm and Tabu Search (HEGATS) to design optimal fuzzy controllers for multi-input multi-output (MIMO) nonlinear system is proposed. The principle of the proposed method is to find the elitism by Genetic Algorithm and to introduce it in the Tabu Search algorithm as initial solution in order to find the optimal fuzzy rule base of the fuzzy controllers. HEGATS is tested for control of a Helicopter Simulator. Simulation results show the effectiveness of the proposed method.

[1]  Nesrine Talbi,et al.  Designing fuzzy controllers for a class of MIMO systems using Hybrid Particle Swarm Optimization and Tabu Search , 2013, Int. J. Hybrid Intell. Syst..

[2]  David E. Goldberg,et al.  Genetic algorithms and Machine Learning , 1988, Machine Learning.

[3]  Kenneth Alan De Jong,et al.  An analysis of the behavior of a class of genetic adaptive systems. , 1975 .

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

[5]  Russell C. Eberhart,et al.  Implementation of evolutionary fuzzy systems , 1999, IEEE Trans. Fuzzy Syst..

[6]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[7]  Fred W. Glover,et al.  Future paths for integer programming and links to artificial intelligence , 1986, Comput. Oper. Res..

[8]  A. M. El-Zonkoly,et al.  Optimal tunning of lead-lag and fuzzy logic power system stabilizers using particle swarm optimization , 2009, Expert Syst. Appl..

[9]  Pierre-Yves Glorennec,et al.  Tuning fuzzy PD and PI controllers using reinforcement learning. , 2010, ISA transactions.

[10]  P. Subbaraj GA Based IFLC Design for an Industrial Process , 2010 .

[11]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[12]  Y. Hori,et al.  Future motion control to be realized by in-wheel motored electric vehicle , 2005, 31st Annual Conference of IEEE Industrial Electronics Society, 2005. IECON 2005..

[13]  Nesrine Talbi,et al.  Designing fuzzy rule base using hybrid elite genetic algorithm and tabu search: Application for control and modeling , 2013, Int. J. Hybrid Intell. Syst..

[14]  K. Dejong,et al.  An analysis of the behavior of a class of genetic adaptive systems , 1975 .

[15]  Potti Subbaraj,et al.  GA Optimized Knowledge Base of FLC for Complex Industrial Process , 2010, J. Digit. Content Technol. its Appl..

[16]  John H. Holland,et al.  Outline for a Logical Theory of Adaptive Systems , 1962, JACM.

[17]  Carlos García-Martínez,et al.  Global and local real-coded genetic algorithms based on parent-centric crossover operators , 2008, Eur. J. Oper. Res..

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

[19]  J. K. Lenstra,et al.  Local Search in Combinatorial Optimisation. , 1997 .

[20]  Ding Jian On the Combination of Genetic Algorithm and Ant Algorithm , 2003 .