Adaptive fuzzy synchronization control for networked teleoperation system with input and multi-state constraints

Constraints are ubiquitous in physical systems, and manifest themselves as physical stoppages, saturation, as well as performance and safety specifications, among others. Violation of the constraints during operation may result in performance degradation, hazards or system damage. In this paper, the synchronization control problem for teleoperation system is investigated with input saturation and multi-state constraints in the presence of system uncertainties and asymmetric time delays. For the multi-state constraints, two types of barriers are considered: constant symmetric barriers and time-varying asymmetric barriers. An auxiliary system is designed to deal with the input saturation problem and the Fuzzy Logic system (FLs) is employed to approximate the system uncertainties. Then, new adaptive fuzzy control algorithms are designed by applying the backstepping method to provide some high performances: faster synchronization speed and higher precision. By constructing the barrier Lyapunov functions (BLF), the stability and synchronization performances are proved with the new control algorithms. Moreover, the system input and system states are prevented from transgressing the constrained region during the transient stages. Therefore, both the steady-state and transient-state performances can be guaranteed. Finally, experiment on two Phantom Premium 1.5A robots is performed to demonstrate the effectiveness of the proposed methods.