無感測器風力再生能源系統之功率追蹤控制:以T-S模糊方法為基礎

Sensorless Power Tracking Control for Renewable Wind Generators Based on T-S Fuzzy Approach

林伯昀(Bo-Yun Lin)

指導教授 ： 練光祐

中原大學/工學院/電機工程研究所/碩士(2006年)

https://doi.org/10.6840/cycu200600376

摘要

再生能源科技快速發展之當下，風力發電系統正受到前所未有的重視。本論文是針對永磁式同步發電機(PMSG)之風力能源轉換系統(WECS)，研究發展最大功率追蹤之控制器。本論文探討如何將(WECS)非線性系統精確表示成T-S模糊模型，並使用智慧型方法用以達成最大功率追蹤，其間兼顧系統的穩定性、指數收斂性質、快速暫態響應、以及強健性等諸多性質的考量。首先，利用系統化方法，將非線性系統精確地表示成T-S模糊模型，少量模糊的規則就足以在一定區域內完整無誤地表示此非線性系統。一個嶄新的控制想法於焉產生:利用虛擬預期變數法來處理追蹤控制的問題，另一方面，以類神經網路調整模糊控制器的等級函數以獲取較快速的暫態響應，此處等級函數，乃源於控制規則的歸屬函數，是利用倒傳遞網路學習取得最佳的數值。我們藉由一些技巧把追蹤控制問題轉換成一個較為簡單處理的穩定性問題，然後先對狀態的可量測做探討。採用此設計方法分成以下兩個步驟: i)根據追蹤目標之輸出方程式和廣義動態的限制條件，求取其虛擬預期變數; ii)採用線性矩陣不等式的方法計算控制器增益。至於穩定性條件則使用Lyapunov法求得，可保證閉迴路系統穩定無虞，此充分條件可轉換成線性矩陣不等式之型式，輔以強有力的數值工具獲得控制增益。由於永磁式同步發電機的無感測器控制是目前發展的趨勢，此論文重點之一是以observer-based設計方式，進行控制器的設計。當我們加入估測器用以重建這些不可量測的狀態，在穩定性的理論分析時，會產生一些擾人的誤差項，然而我們發現模糊模型的歸屬函數其實滿足Lipschitz條件，所以估測增益與回授增益可以分開求取，至此無感測控制器之設計，乃可以不致太複雜的過程中得以圓滿解決。上述提出之控制方法均以某一型WECS的實際數值加以驗證，而成效良好。

關鍵字

線性矩陣不等式 ； 虛擬預期變數 ； 估測器 ； 風力能源轉換系統 ； 永磁式同步發電機 ； 平行分佈補償

並列摘要

Among the fastest-growing renewable energy technologies, wind power is gaining much more attention then ever before. This thesis deals with the maximum power tracking control for the permanent magnet synchronous generator (PMSG) of a wind energy conversion system (WECS). This thesis discuses how to exactly represent the (WECS) nonlinear system as a T-S fuzzy model, and uses intelligent control to achieve maximum power tracking, moreover, the stability, exponential convergence property, fast transient response, and properties like robustness are taken into considerations. First of all, a systematic method is given to represent a nonlinear system exactly as a T-S fuzzy model which can accurately represent the nonlinear system under a certain region with a few fuzzy rules. A brand new control idea is brought up: Using virtual desired variables (VDVs) to deal with the tracking control problems, on the other hand, BP-learning algorithm of neural network is used to adjust the grade function of the fuzzy controller to achieve faster transient responses. Tracking control is technically transformed into a much simple stabilization problem. Then the design procedure is split into two independent steps: i) Determine the VDVs from the desired output equation and the generalized kinematic constraint; ii) Determine the control feedback gains by solving a set of LMIs. Lyapnunov’s method is used to obtain the stability conditions which insure the stability of the closed loop system, these adequate conditions can be transformed as LMIs and solved using powerful numerical methods to obtain the control gains. Since sensorless controller design of PSMG is a trend, we focus on observer-based controller design in the second part of the thesis. When observers are implemented to re-establish the immeasurable states, some disturbing terms will arise on stability analysis. However, we discovered that the membership functions of fuzzy model still satisfy a Lipschitz-like property; therefore, observer gain and controller gain can be obtained separately. To this point, sensorless controller design process is solved in less complicated and satisfactory way. Above controlling techniques are verified under the actual parameters of a certain type of WECS and result in very nice performance.

並列關鍵字

LMIs ； VDVs ； WECS ； Observer ； PMSG ； PDC

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