基于模糊数学的控制系统鲁棒性分析模型仿真  

Analysis Model Simulation of Control Robustness System Based on Fuzzy Mathematics

作　　者：宫玉荣[1] 

机构地区：[1]郑州成功财经学院,河南巩义451200

出　　处：《科技通报》2016年第2期10-14,共5页Bulletin of Science and Technology

基　　金：河南省2015年度科技发展计划项目课题(编号:152102210027)

摘　　要：对复杂非线性控制系统的鲁棒性进行分析在工控领域具有重要的应用价值。传统算法无法避免复杂非线性系统中参数的动态变化性、建模误差大的特点,难以进行有效分析。为此提出一种基于模糊数学的控制系统鲁棒性控制方法。将复杂的非线性控制系统转换为简单的积分过程进行处理,并通过对误差的积分和系统输出的比例的调整转变为一个线性系统,能够避免复杂非线性控制模型必须具有显性解的局限性,将模糊规则的控制方法与神经网络相结合,并对控制参数能够进行动态调整,从而得到精确的控制效果。仿真实验结果表明,改进算法在复杂非线性系统中具有更高的鲁棒性,效果令人满意。The robustness of the control system of complex nonlinear analysis has important application value in the field of industrial control .Traditional algorithms can't avoid the complex nonlinear system parameters in the dynamic change of sex, modeling of the characteristics of big error is difficult to effective analysis. Therefore put forward a kind of control system robust control based on fuzzy mathematics method. Converts complicated nonlinear control system simple integral process for processing, and through the integral of error and the adjustment of the ratio of the system output into a linear system, to avoid the complex nonlinear control model must have a explicit solution of the limitations, the rules of the fuzzy control method combined with neural net work, and the control parameters can be adjusted dynamically, and precise control effect is obtained. The simulation experimental results show that the improved algorithm in the complex nonlinear system has higher robustness sand satisfactory effect.

关 键 词：模糊数学 控制系统 鲁棒性 

分 类 号：O23[理学—运筹学与控制论]