School of Innovation and Entrepreneurship, Xi'an Fanyi University, Xi'an 710105, China.
School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, China.
Sensors (Basel). 2021 Nov 9;21(22):7443. doi: 10.3390/s21227443.
A bilateral neural network adaptive controller is designed for a class of teleoperation systems with constant time delay, external disturbance and internal friction. The stability of the teleoperation force feedback system with constant communication channel delay and nonlinear, complex, and uncertain constant time delay is guaranteed, and its tracking performance is improved. In the controller design process, the neural network method is used to approximate the system model, and the unknown internal friction and external disturbance of the system are estimated by the adaptive method, so as to avoid the influence of nonlinear uncertainties on the system.
设计了一种双边神经网络自适应控制器，用于一类具有恒定时滞、外部干扰和内部摩擦的遥操作系统。保证了具有恒定通信信道时滞和非线性、复杂、不确定恒定时滞的遥操作力反馈系统的稳定性，并提高了其跟踪性能。在控制器设计过程中，采用神经网络方法对系统模型进行逼近，采用自适应方法对系统未知的内部摩擦和外部干扰进行估计，从而避免了非线性不确定性对系统的影响。
