基于自适应思维进化算法的容错控制仿真研究

Simulation Research of Fault-Tolerant Control Based on Adaptive Mind Evoltionary Algorithm

思维进化计算(Mind Evolutionary Computation,MEC)是一种新型的智能计算方法,能有效地克服遗传算法中存在的一些缺陷,但也存在着进化速度较慢的不足之处。为了提高思维进化计算的进化速度,在该算法中引入了三个自适应因子,建立了一种自适应思维进化算法(Adaptive Mind-Evolutionary Algorithm,AMEA)。基于自适应思维进化算法,构造了一种自适应思维进化容错控制(Adaptive Mind-Evolutionary Fault-Tolerant Control,AMEFTC)系统,可实现控制律的在线重组,使系统在发生故障后仍能维持正常系统的静态和动态性能,从而实现了对系统故障的容错控制,最后通过仿真实例验证了这一控制律重组容错方案的可行性和有效性。

Mind evolutionary computation （MEC） is a novel intelligent computing algorithm. It can effectively avoid some essential drawbacks of genetic algorithm （GA）, but yet there exists disadvantage of slow evolution speed in MEC. In order to increase the evolution speed of MEC, an adaptive mind-evolutionary algorithm （AMEA） was proposed via introducing three adaptive factors. An adaptive mind-evolutionary fault-tolerant control （AMEFTC） system, which could reconfigure the control law on-line, was constructed based on AMEA, and this fault-tolerant control system could guarantee normal static and dynamic characteristics of system when faults occurred within the system. Feasibility and effectiveness of the above fault-tolerant strategies were demonstrated by simulation examoles.