针对异步电动机驱动系统中存在的负载扰动和参数不确定的问题,本文在传统自适应反步控制方法的基础上,运用神经网络逼近系统模型中未知的非线性函数,同时采用命令滤波技术,解决了传统反步法中对虚拟控制函数进行连续求导而无法避免的计算爆炸问题,实现对异步电动机的速度调节控制。为了验证本文所提方法的有效性,在Matlab环境下对异步电动机进行仿真分析,仿真结果表明,即使在参数不稳定和有负载转矩扰动的情况下,本文所提出的控制方法依然可以很好的跟踪给出的期望信号,并确保跟踪误差收敛到原点很小的邻域内,可实现对异步电动机快速有效的控制。因此,该方法具有一定的实际应用价值。
This paper developed an adaptive neural networks(NNs)command filtered control approach to speed regulation for induction motors with parameter uncertainties and load torque disturbance.Neural networks are used to approximate unknown nonlinear functions and the adaptive command filtered backstepping is employed to construct controllers.Therefore,the proposed control method can overcome the problems of"nonlinear systems with parameter uncertainties"and "explosion of complexity"inherent in the traditional backstepping design.Simulation results show that the proposed control approach can make perfect tracking performances under the parameter uncertainties and load torque disturbance,and guarantee the tracking errors can converge to a small neighborhood of the origin.