| Summary: | 碩士 === 中原大學 === 電機工程研究所 === 101 === This thesis uses neural network and sliding mode control to design controller for a three dimensional overhead crane system. The control objectives are to move the load to the target as fast as possible and to avoid load swing of the crane system. Based on the principles of decoupling sliding surface function and self-tuning algorithm of the sliding slope parameters, this thesis presents a new sliding surface function combined with neural network to improve the approaching mode of the sliding mode control, and reaction time. So, the system has robust properties at the approaching mode and sliding mode. Also, the equivalent control based on neural network not only avoids computing the complex inverse dynamic control, but also performs the accurate system parameters. The stability of the proposed control scheme is also guaranteed. Finally, performance of the proposed method is demonstrated by some simulation results.
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