A modified genetic algorithm for neurocontrollers

Genetic algorithtiis are getting more popular nowadadvs because of their sirtiplicity and robustness. Genetic algorithm are global search techniques for optimizations and many other problems. A feed-forward neural network that is widely used in control applications usually learns by back propagation afgorithm(BP). However, when there exist certain constraints, BP cannot be applied. We apply a genetic algorithtti to such a case. To ittiprove hill-climbing capability and speed up the convergence, we propose a tnodified genetic algorifhnr(i2fGA). The validity and efficiency of the proposed algorithtti, hlG.4 are shown by various sitnulation examples of systetti identification and nonlinear svsteiti control such as cart-pole system and robot manipulators

[1]  Nostrand Reinhold,et al.  the utility of using the genetic algorithm approach on the problem of Davis, L. (1991), Handbook of Genetic Algorithms. Van Nostrand Reinhold, New York. , 1991 .

[2]  Atam P. Dhawan,et al.  Use of genetic algorithms with backpropagation in training of feedforward neural networks , 1993, IEEE International Conference on Neural Networks.

[3]  C.W. Anderson,et al.  Learning to control an inverted pendulum using neural networks , 1989, IEEE Control Systems Magazine.

[4]  C. L. Karr,et al.  Fuzzy control of pH using genetic algorithms , 1993, IEEE Trans. Fuzzy Syst..

[5]  D. E. Goldberg,et al.  Genetic Algorithm in Search , 1989 .

[6]  Richard S. Sutton,et al.  Neuronlike adaptive elements that can solve difficult learning control problems , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[7]  Guy Albert Dumont,et al.  System identification and control using genetic algorithms , 1992, IEEE Trans. Syst. Man Cybern..

[8]  David B. Fogel,et al.  Evolving neurocontrollers using evolutionary programming , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

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

[10]  Yoshiaki Ichikawa,et al.  Neural network application for direct feedback controllers , 1992, IEEE Trans. Neural Networks.