| Summary: | 碩士 === 國立臺灣科技大學 === 機械工程系 === 88 === Since, pneumatic systems have the advantages of low-cost, clean, safety, and operating compliance, they have been wildly used in industrial automation equipments for on-off operations. However the pneumatic system has highly nonlinear behavior due to the air compressibility. It is difficult to derive a model-based positioning controller for the accurate position control application, especially when the pneumatic system has coupling effect for a multi-degree system.
The dynamic behavior of a pneumatic system was influenced significantly by the pneumatic structure and the coupling effect among multi-axis synchronous control. It will increase the complexity of the pneumatic system positioning control. In addition, the dynamic behavior is too complicated to establish an appropriate dynamic model for a model based controller design.
In this research, three model-free intelligent controllers: (1) self-organizing fuzzy controller (SOFC), (2) adaptive fuzzy sliding mode controller (AFSMC), and (3) adaptive radial basis function sliding mode controller (ANSMC), were implemented on a four-leg pneumatic table leveling control to handle the system nonlinear and coupling uncertainty by on-line learning laws. The experiment results show that the stability and robustness of this MIMO nonlinear system can be achieved by using these controllers. The experimental results also show that the acceptable dynamic control performance was obtained by using these intelligent controllers.
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