【摘要】 研究一类非线性不确定时滞系统的滑模变结构控制,针对包含不确定性及时滞的非线性系统,对其标称部分和不确定部分分别设计控制律,提出的控制方案能保证闭环系统的渐近稳定.考虑当系统具有不确定性和时滞部分模型未知时,采用RBF神经网络对其逼近,得出基于RBF神经网络的滑模变结构自适应控制方案.该方案能有效降低系统的抖振,基于Lyapunov理论证明了控制方案的可行性,仿真结果表明了该方案的有效性.更多还原

【Abstract】 An adaptive sliding mode controller for a class of nonlinear uncertain system with time-delay is proposed in this paper. According to the system which contained uncertainties and time-delay, the controller is proposed by design for the uncertainties and time-delay. The controller can stabilize the whole system. The RBF neural network is used to approximate the lumped uncertainties and time-delay of the nonlinear systems. The controller obtained by using RBF neural network eliminated system chattering effectively. Stability analysis is also given by using Lyapunov function. Simulation results demonstrate the effectiveness of the method.更多还原