基于系统辨识的非线性系统滑模变结构控制

针对一类非线性系统，提出了一种基于神经网络系统辨识的滑模变结构控制方法。用2个神经网络来动态辨识系统对象，结合变结构控制，克服了常规变结构控制方法中被控制对象变化范围的限制。仿真结果表明，控制系统具有良好的稳定性、收敛性，同时抖动也有所减少，具有较强的鲁棒性。

Sliding mode variable structure control of nonlinear system based on system identification

Aiming at first kind of nonlinear system, a sliding mode variable structure control method based on system identification by using of neural network was proposed. The controlled system object was dynamically identified by two neural networks. Combining with variable structure control, the limit of variation range for controlled object in the conventional variable structure control was overcome. The simulation results show that the control system has good stability and convergence, meanwhile, system chattering is reduced and good robustness is achieved.