自学习模糊滑模控制及其在电液伺服系统中的应用

针对一类不确定性非线性系统的跟踪控制问题,应用模糊逻辑系统来逼近滑模的等价控制,提出了一种具有自学习能力的模糊滑模控制方法。通过在线学习,动态地更新模糊控制的规则,使得模糊控制的输出沿使滑模渐近稳定的方向逐步逼近滑模的等价控制,证明了自学习模糊滑模控制系统在李雅普诺夫意义下的渐近稳定。把这种方法应用于电液伺服系统的跟踪控制,仿真和实时控制结果表明:该方法明显优于常规滑模控制并能获得满意的跟踪精度和稳定性。

SELF-LEARNING FUZZY SLIDING- MODE CONTROL AND ITS APLICATION TO ELECTROHYDRAULIC SERVO SYSTEMS

An approach of self-learning fuzzy sliding-mode control , which uses the fuzzy logic systems to approximate sliding-mode equivalent control, is presented for the tracking control of a class of systems with the nonlinear and parameter uncertainties. The fuzzy control rules are updated through on-line learning, which make the output of fuzzy control approach sliding-mode equivalent along the direction of making sliding-mode asymptotic stable. The asymptotic stability of self-learning fuzzy sliding-mode control systems is proved based on Lyapunov theory. The proposed method is applied to an electrohydraulic servo systems, the results of simulation and experiment of real-time control show that the proposed method is distinctly excelled than that of conventional sliding-mode control and satisfied control precision and stability can be obtained.