Adaptive Neural Network Control of Time Delay Teleoperation System Based on Model Approximation
Yaxiang Wang, Jiawei Tian, Yan Liu, Bo Yang, Shan Liu, Lirong Yin, Wenfeng Zheng
Abstract
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.
Topics & Concepts
TeleoperationControl theory (sociology)Nonlinear systemInternal modelController (irrigation)Artificial neural networkConstant (computer programming)Adaptive controlStability (learning theory)Computer scienceControl engineeringProcess (computing)Time constantChannel (broadcasting)EngineeringRobotControl (management)Artificial intelligenceOperating systemMachine learningComputer networkQuantum mechanicsBiologyProgramming languageElectrical engineeringPhysicsAgronomyAdvanced Technologies in Various FieldsTechnology and Human Factors in Education and HealthAdvanced Technologies and Applied Computing