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针对参数不确定非线性系统 ,提出了基于回归神经网络的间接自适应控制律。控制器采用滑模变结构技术 ,能保证系统对外部扰动和参数不确定性的不敏感性 ,最后给出的仿真实例证实了模型的适应性
For nonlinear systems with parameter uncertainty, an indirect adaptive control law based on regression neural network is proposed. The controller adopts the sliding mode variable structure technology to ensure the insensitivity of the system to external disturbances and parameter uncertainties. Finally, the simulation example is given to confirm the adaptability of the model