Tracking control of motion systems via a wavelet neural network and sliding-mode technology
| Autor: | Jun-Sheng Zhao, 趙俊聲 |
|---|---|
| Rok vydání: | 2014 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 102 In this thesis, a wavelet neural network (WNN)-based sliding mode control strategy is investigated to resolve the tracking control problem of motion systems. The proposed control system comprises of an adaptive wavelet controller and a robust controller. The adaptive wavelet controller acts as the main tracking controller, which is designed via a WNN to mimic the merits of ideal sliding mode control law. The adaptation laws of the motion control system are derived from the Lyapunov stability theorem, which are utilized to update the adjustable parameters of WNN on-line for further assuring system stability. Moreover, based on control technique, the robust controller is developed to attenuate the effect of the approximation error caused by WNN approximator, so that the desired tracking performance can be achieved. Finally, two motion systems, the wing rock system and the three-links robotic system, are performed to verify the effectiveness and robustness of the proposed control strategy. Furthermore, the salient merits are also indicated in comparison with the sliding mode control system. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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