以數位訊號處理器實現智慧型氣動馬達速度控制系統
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2015
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Abstract
本論文之目標為設計智慧型控制系統以對葉片式氣動馬達伺服系統進行速度控制。在論文中，首先對氣動馬達之構造及運作原理進行討論，接著分析氣動馬達系統之數學動態，以推導出氣動馬達之標準二階狀態方程式。由於氣動馬達之動態特性及系統參數為高度非線性且時變，為了在既有的非線性特性及外部擾動情況下仍能達到高精準度之速度控制，本論文提出了基於比例積分微分型模糊類神經網路與適應性動態滑動模式兩種智慧型控制系統作為氣動馬達之速度控制器。最後，本論文以具32位元浮點數運算能力之數位訊號處理器TMS320F28335實現所提出的控制系統。實驗結果顯示以本論文所提出之兩種智慧型控制系統對氣動馬達均能達到有效之速度控制。
The object of this study is to design intelligent control systems for controlling the speed of a vane-type air motor (VAM) pneumatic servo system for tracking reference speed command. First, the structure and operating principles of the VAM servo system are introduced. Then, the dynamics of the VAM servo system is analyzed to derive the second order state equation of the VAM. Moreover, due to the dynamic characteristics and system parameters of the VAM servo system are highly nonlinear and time-varying, intelligent controllers control systems including proportional-integral-derivative-based fuzzy neural network (PID-based FNN) and adaptive dynamic sliding-mode control (ADSMC), are proposed to achieve precise speed control of VAM servo system under the occurrences of the inherent nonlinearities and external disturbances. Finally, a 32-b floating-point digital signal processor (DSP) TMS320F28335 was adopted for implementing the proposed control systems. The experimental results demonstrated the validities and advantages of the proposed PID-based FNN and ADSMC systems for the VAM servo system.
The object of this study is to design intelligent control systems for controlling the speed of a vane-type air motor (VAM) pneumatic servo system for tracking reference speed command. First, the structure and operating principles of the VAM servo system are introduced. Then, the dynamics of the VAM servo system is analyzed to derive the second order state equation of the VAM. Moreover, due to the dynamic characteristics and system parameters of the VAM servo system are highly nonlinear and time-varying, intelligent controllers control systems including proportional-integral-derivative-based fuzzy neural network (PID-based FNN) and adaptive dynamic sliding-mode control (ADSMC), are proposed to achieve precise speed control of VAM servo system under the occurrences of the inherent nonlinearities and external disturbances. Finally, a 32-b floating-point digital signal processor (DSP) TMS320F28335 was adopted for implementing the proposed control systems. The experimental results demonstrated the validities and advantages of the proposed PID-based FNN and ADSMC systems for the VAM servo system.
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Keywords
氣動馬達, 速度控制, 數位訊號處理器, 滑動模式控制, 類神經網路, air motor, speed control, digital signal processor, sliding-mode control, neural network