Adaptive-neural command filtered synchronization control of tele-robotic systems using disturbance observer with safety enhancement.

Due to the nature of the tele-robotic systems, some main problems are imposed, such as external disturbances, time-varying delays and external torques. However, some applications such as tele-surgery systems, require high precision, safety and accurate transmission of information between the leader and follower robots. In order to facilitate the imposed restrictions and to guarantee transient-state, and even steady-state performances in the presence of external disturbances and system uncertainties, the time-varying full state constrained control is employed by applying the Barrier Lyapunov function (BLF). In this regard, a new adaptive neural network torque observer is proposed to make the system independent from the force sensors. Moreover, the independence of the proposed algorithm from perfect knowledge of the manipulator dynamics and time-delay's derivative of communication channels are advantages of this paper. Furthermore, the key idea of this paper is to lessen the computational complexity in the backstepping-based adaptive neural controller by means of the command filter strategy and the BLF approach is combined to converge the synchronization error signals into a predefined constraint. In order to consider practical limitations, time-varying delays in the communication channel and input saturation constraint are also considered in the design mechanism. Finally, the stability analysis of the observer and controller together is conducted and the evaluation of the performance of the proposed method is performed through a series of various scenarios and comparisons. • Design of a new adaptive neural network disturbance observer to relax the system from force sensors. • Safety enhancement with equipping the proposed algorithm to the full state constraints. • Considering the input saturation and time-varying delay in the design mechanism. • Design an auxiliary system to deal with input saturation limitation. • Employing the command filter strategy with error compensation signals to handle the time delay's derivatives. [ABSTRACT FROM AUTHOR]