On the Design of Observer-based Dynamic Visual Servo Systems via Nonlinear H_∞ Model Predictive Control

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In this research, we consider the design of observer-based dynamic visual servo systems via nonlinear H_∞ model predictive control. Firstly, the 3-D visual feedback control problem is established as the robot control problem and the estimation problem of the relative rigid body motion between the camera and the target object. For this problem, we propose a nonlinear H_∞ model l)redicti~7e control law for the visual servo systems. Specifically, the appropriate energy function to the proposed control law plays an important role in the control design.Secondly, the dynamic visual servo system is constructed from a robot manipulator, a camera and an image processing board with a. high-performance DSP and a. real-time system. While we provide real-time software for implementing the proposed control law to the real system, the algorithm for optimal problems is considered in order to calculate the controller by the real system.Finally, we have experiments for evaluating the control performances using the constructed dynamic visual servo system. Experimental results are analyzed exactly by a high-performance workstation. Not only the states of the average but also the states of the worst case are considered in order to verify the proposed control law with experimental results systematically. Moreover, the real-time software and the algorithm for optimal problems are reconsidered via, simulations and experiments.