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本文利用干扰观测器和Backstepping方法,提出了一类不确定非线性系统的鲁棒自适应控制方案.首先,利用径向基神经网络(radial basis function neuralnetwork,RBFNN)设计干扰观测器,并通过对RBFNN参数的自适应调整来逼近系统干扰.基于干扰观测器的输出,采用Backstepping方法设计鲁棒自适应控制器.在所设计的鲁棒自适应控制器作用下,闭环系统所有信号达到半全局一致有界稳定.闭环系统稳定分析表明适当地选取设计参数可以确保所有系统状态是一致有界的.最后,仿真结果验证了所提出的鲁棒自适应控制方案的有效性.
In this paper, a robust adaptive control scheme for a class of uncertain nonlinear systems is proposed by using disturbance observers and Backstepping methods. First, a disturbance observer is designed by using radial basis function neural network (RBFNN) RBFNN parameters are used to approximate the system disturbance.Based on the output of the disturbance observer, a robust adaptive controller is designed by Backstepping method.All the signals in the closed-loop system reach semi-global consistency under the effect of the robust adaptive controller Bounded stability The stability analysis of the closed-loop system shows that proper selection of the design parameters ensures that all system states are uniformly bounded.Finally, the simulation results verify the effectiveness of the proposed robust adaptive control scheme.