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In this paper, a mixed controller for solving the trajectory tracking and point stabilization problems of a mobile robot is presented, applying the integration of backstepping technique and neural dynamics. By introducing a virtual target point, the whole motion process is divided into two parts. The first one is employed to realize tracking control and the other one is adopted to implement point...
In this study, a controller for robotic motion based on neuroscientific principles was developed and implemented using an artificial neural element and a conventional robotic arm. With independent control over arm final position, velocity, acceleration, and deceleration, this system offers a more smooth, efficient and life-like motion than conventional open-loop methods. The system makes use of a...
This paper presents a neural network motion tracking control methodology for piezo-actuated flexure-based micro-/nanomanipulation mechanisms. In particular, the radial basis function neural networks are adopted for function approximations. The control objective is to track desired motion trajectories in the presence of unknown system parameters, nonlinearities including the hysteresis effect, and...
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