Research of Bearing-Less Switched Reluctance Motor's Control Based on Chaos Optimization Algorithms

Aiming at the requirements of high accuracy and fast response of bearing-less switched reluctance motor's control system,the control project of fuzzy neural network(FNN) based on chaos optimization algorithms was expounded. The parameters of FNN controller were optimized with the chaos optimization tactics which adopted the combination of thick searching and thin searching,the concrete device methodology and optimization steps given. Emulation effects show that this bearing-less switched reluctance motor's control system has no vibration and overshoot with high accuracy,strong robustness and anti-disturbance.