Decentralized fault-tolerant control of modular robot manipulators with actuator saturation: neural adaptive integral terminal sliding mode-based control approach

Abstract A novel neural adaptive integral terminal sliding mode control for decentralized fault-tolerant strategy, including the surface, nonlinear disturbance observer, radial basis network and robust controller, is presented in this paper to achieve of modular robot manipulators. First, designed controller. Then, boost performance controlled system, observer are introduced approximate terms disturbances. The reconstructed uncertainty term applied as compensation. Next, super-twisting technique employed compensate estimation errors ensure stability. In addition, actuator saturation problem, function network-based compensation proposed. Finally, stability closed-loop robotic system demonstrated based on Lyapunov theory. Computer simulations verified efficiency advantages approach.