Design of single neuron PID multi-variable controller based on evolving PSO
暂无分享,去创建一个
Coupling multi-variable controller contains some problems of complex nonlinear control. Single neuron PID controller has a good capability of self-adapting, self-learning, nonlinear and robustness. This paper uses some single neuron PID controllers to design coupling multi-variable controller, accompanying a large amount of optimization problem of nonlinear multi-dimension complex function. To solve that problem, evolving PSO has been proposed in this paper. To ravel out particle swarm optimizationpsilas (PSO) problem of local minima, crossover and mutation operations have been added to it. Simulation experiments of two typical objects have been made, and demonstrate the effectiveness and superiority of the proposed algorithm. This designed controller has a good performance. Evolving PSO can solve the complex problem in this controller design effectively.
[1] R. Gorez. A survey of PID auto-tuning methods : Feature issue controller tuning , 1997 .
[2] James Kennedy,et al. Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.
[3] Russell C. Eberhart,et al. Parameter Selection in Particle Swarm Optimization , 1998, Evolutionary Programming.