- 學位論文
以適應性及模糊為基礎之線性感應馬達控制
Linear Induction Motor Control Based on Adaptive and Fuzzy Approaches
摘要
本論文主要以適應性控制及T-S 模糊模型控制之方法討論線性感應馬達之速度控制問題。為達到具有強健性之速度控制及無速度感測器之速度控制目的，我們以循序漸進的方式進行討論。首先，與以往研究不同之處是將邊際效應考量在線性感應馬達的數學模型之中，並以此數學模型為基礎來設計不同的控制器。設計過程中為達到最佳推力，首先設想二次側磁通的理想值為固定常數大小。接著，考慮實際的電流饋送條件下，在電流誤差不為零的情形下可達成速度及位置追蹤控制，相較於傳統理想的電流饋送控制方式可獲得較寬鬆的條件。本論文提出一個新的強健適應性控制方法稱為Adaptive VDV，藉以處理參數的不確定性，其中包含未知的邊際效應及二次側電阻。更多的實際條件，包含有界的一次側電壓及有限絕對-積分電流追蹤誤差均被納入考慮，吾人所設計的控制器依然能達到漸進速度追蹤與漸進位置追蹤的效果。另外，為避免使用昂貴的速度感測器，我們探討無需感測器的速度控制。為此目的，透過T-S模糊理論，將非線性的線性感應馬達模型表示成T-S模糊形式。接著，建立估測器用以估測速度及二次側磁通，其中所設計的估測器增益可透過求解線性矩陣不等式得到。結合模糊估測器與VDV概念，其估測誤差及追蹤誤差將會指數收斂到零。最後，我們提出以T -S模糊模型為基礎之VDV的控制器設計方式，用於T-S模糊估測器及控制器的設計。詳細的設計流程分成以下兩個步驟進行：1）根據追蹤目標之輸出方程，決定虛擬命令變數（VDV）；2）採用線性矩陣不等式方法分別求解估測器增益及控制器增益。以模糊模型為基礎之VDV設計方式具有嚴格的穩定性分析及方便設計增益值等優點。從模擬及實做結果顯示，不論是在適應性控制或T-S模糊無感測器控制都有令人滿意的效能。
並列摘要
This dissertation presents a speed control issue for linear induction motors (LIMs) under features of adaptive control and T-S fuzzy model based control. A gradual progress is done to achieve robust sensor-based speed control and sensorless speed control. First of all, the end-effect is taken into our consideration for linear induction motor (LIM) modeling in contrast to former researches. After the LIM model is derived, optimal force property is mentioned by a constant secondary flux and is further applied in the controller design process. Then the speed/position tracking control is achieved under a practical current-fed condition with residual current errors which is more relaxed than traditional ideal current-fed control. The novel robust adaptive control scheme called adaptive VDV (virtual desired variable) synthesis is carried out to deal with the existence of parametric uncertainty including unknown end-effect and secondary resistance. More practical conditions including boundary primary voltage and finite absolute-integral of current tracking is considered; however, the proposed controller still achieves asymptotic speed and position tracking. Furthermore, the effect of residual current errors is attenuated in an L₂-gain sense. In addition, we probe into the issue of sensorless speed control to avoid using expensive sensors. To this end, the nonlinear LIM is represented in T-S fuzzy form. Next, an observer is constructed to estimate the immeasurable states of mover speed and secondary flux, where the observer gains are obtained by solving a set of linear matrix inequalities (LMIs). Combination of the fuzzy observer and VDV-synthesis concept leads to exponential speed tracking. Finally, the T-S fuzzy model-based VDV controller is proposed by applying the T-S fuzzy observer and controller design. In detail, the design procedure is in two independent steps: 1) determine the virtual desired variables from desired output equations; 2) determine the control feedback gains and observer gains by independently solving a set of LMIs. The benefits of the fuzzy model-based VDV design is resulting a strict overall stability analysis and easy gain design. The simulations and experiments results show the satisfactory performance in both adaptive control and T-S fuzzy sensorless control.
參考文獻
延伸閱讀
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