This brief proposes a method for designing a disturbance observer (DOB) to decouple joint interactions in robot dynamics with nonlinearity. The traditional DOB based on filter design theory has limited performance since the cut-off frequency of its Q-filter is the only tunable parameter to deal with disturbance suppression and model uncertainty. In this brief, a robust optimal design method is developed for the DOB, which can achieve optimal performance of suppressing disturbance by systematically shaping its Q-filter. Simulation results of application to a two-link manipulator with flexible joints show the improvements in disturbance suppression, which illustrates the validity of the proposed method.
IndexTerms-Disturbance observer (DOB), H ∞ standard control problem, low-pass filter, robust motion control, two degrees-of-freedom. I. INTRODUCTION I T IS ESSENTIAL to improve the robustness of a motion control system to external disturbance and parameter variations. Disturbance observer (DOB)-based control is one of the most popular methods to attain this purpose [1]. Recent results in experiments and applications have shown the effectiveness of DOB based control [2]-[6]. Especially, it is widely used to decouple the interactive model of robot manipulator, compensate its nonlinearity, and improve the speed and accuracy of control [7]. The DOB for this purpose is often designed by traditional filter models such as binomial model and Butterworth model [8]-[10], but these model have cutoff frequency as the only tunable parameter. In these models, To improve the performance of suppressing disturbance, the cutoff frequency should be increased. However, because of the existence of high frequency model uncertainty caused by flexibility of joint shafts and change of load etc., the cutoff frequency is restricted to guarantee robust stability. This is a substantial disadvantage of using conventional filter model.Recently, several design methods of DOB using H ∞ control scheme have been reported, which can provide optimal performances of rejecting disturbance and sensor noise on the condition of guaranteeing robust stability to parameter uncertainty. However, most of the methods employ numerical computation algorithms to obtain optimal Q-filter [11]-[13]. A systematic and straightforward method is proposed in [14],
A telepresence system enables a user in a local environment to maneuver in a remote or virtual space through a robotic operator (agent). In order to ensure a high degree of telepresence realism, it is critical that the local user has the ability to control the remote agent's movement through the user's own locomotion. The required motion of the remote agent is determined according to its environment and the specific task it is to perform. The local user's environment is usually different from that of the remote agent in terms of the shapes and dimensions. A motion mapping is needed from the remote agent to the local user to ensure the similarity of the paths in the two environments. In particular, the terminal position of the local user after a segment of movement is also an important portion in such a motion mapping. This paper progressively addresses these issues from the optimization point of view. Two strategies are suggested for solving the motion mapping problem for the single user case. The resulting solutions are then extended to the multiuser case where several local users share a local environment to control different remote agents. Extensive simulations and comparisons show the feasibility and effectiveness of the proposed approaches.
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