In the present paper, an active disturbance rejection control(ADRC) scheme via radial basis function(RBF) neural networks is designed for adaptive control of non-affine nonlinear systems facing hysteresis disturbance in which RBF neural network approximation is utilized to tackle the system uncertainties and ADRC is designed to real-time estimate and compensate disturbance with unknown backlash-like hysteresis. Combining the adaptive neural networks design with ADRC design techniques, a new dual-channel composite controller scheme is developed herein whereby adaptive neural networks are used as feed-forward inverse control and ADRC as closed-loop feedback control. Furthermore, as compared to adaptive neural networks control algorithm, the proposed RBF-ADRC dual-channel composite controller can guarantee that the desired signal can be tracked with a small domain of the origin and it is confirmed to be effective under Lyapunov stability theory and MATLAB simulations.

本文针对径向滞后扰动的非仿射非线性系统，设计了一种基于径向基函数（RBF）神经网络的主动扰动抑制控制（ADRC）方案，利用RBF神经网络逼近来解决系统的不确定性。 ADRC旨在实时估计和补偿具有未知反冲状磁滞的干扰。将自适应神经网络设计与ADRC设计技术相结合，在此开发了一种新的双通道复合控制器方案，其中自适应神经网络被用作前馈逆控制，而ADRC被用作闭环反馈控制。此外，与自适应神经网络控制算法相比，