一类不确定执行器非线性系统的自适应控制

针对一类带不确定执行器非线性的控制系统,提出了一种自适应神经网络控制方法。建立了包括死区、齿隙和“类齿隙”磁滞特征的非线性执行器模型。通过结合所建立的模型和Nussbaum增益技术,解决了当执行器非线性不确定时的控制问题。所设计的方案不需知道非线性特征参数边界,并且当非线性特征为死区时,其坡度可以为时变的。引入了自适应补偿项消除建模误差和干扰的影响。仿真结果验证了该方法的有效性。

Adaptive control for a class of nonlinear systems with uncertain actuator nonlinearity

An adaptive neural network control method is proposed for a class of control systems with uncertain actuator nonlinearity. A model for the nonlinear actuator is developed which includes the characteristics of dead zone, backlash and “backlash-like” hysteresis. By combining the developed model and the Nussbaum gain technique, the problem of uncertain actuator nonlinearity is solved perfectly. The proposed scheme does not require the prior knowledge on the bounds of parameters of the motioned characteristics, and the slopes of dead zone can be time variant when dead zone nonlinearity is concerned. The adaptive compensation term is adopted to minify the influence of modeling error and external disturbance. Simulation results are presented to demonstrate the effectiveness of this method.