具有快速變化延遲與封包遺失特性之網路控制系統區間型Type-2 T-S控制器設計

Interval Type-2 T-S Fuzzy Controller Design for Networked Control Systems with Fast-Varying Delay and Packet Loss

鄭為中(Wai-Chung Cheng)

指導教授 ： 曾傳蘆

國立臺北科技大學/電資學院/電機工程系研究所/碩士(2010年)

摘要

由於網際網路具有傳輸延遲和封包遺失的特性。為了解決此問題，本論文考慮傳輸延遲和封包遺失的網路控制系統，並對其進行穩定度分析與控制器設計。
首先，我們採用區間型Type-2 T-S糊模系統將網路控制系統模式化，並採用平行分佈補償法的概念來設計區間型Type-2 T-S模糊控制器，其歸屬函數適合度可利用類神經網路調整。在穩定度分析方面，則由選定的李亞普若夫泛函，推導出系統的穩定條件，該條件不需受限於延遲變化率的上限小於一，表示延遲在給定的範圍內可快速變化。利用上述條件，本研究推導出新的控制器設計方法並將其轉換為線性矩陣不等式型式，使用Matlab LMI Toolbox可解得所需的控制器增益矩陣。此外，本論文使用仿電磁吸斥優化演算法搜尋網路控制系統時間延遲容忍上限，以增強網路控制系統的控制效果。
最後，根據本論文所提出穩定度分析及控制器設計的結果，利用數值範例進行模擬與討論。模擬結果驗證了本論文所提出模糊控制器設計理論的正確性與性能。

關鍵字

區間型Type-2 T-S模糊模型 ； 網路控制系統 ； 快速時間延遲 ； 類神經網路 ； 李亞普若夫泛函 ； 仿電磁吸斥優化演算法

並列摘要

The networked control systems have the characteristics of data-transmission delay and packet loss. In order to resolve the problem, this thesis investigates the stability analysis and controller design by using type-2 T-S fuzzy theory.
Firstly, the networked control systems are modeled as the dynamic interval type-2 T-S fuzzy systems. The concept of parallel distributed compensation (PDC) is then used to design the corresponding interval Type-2 T-S fuzzy controllers. In addition, this thesis uses artificial neural network to adjust the fitness of membership function of the interval Type-2 T-S fuzzy controller. For the system stability analysis, the stability condition is derived using a selected Lyapunov functional. This condition releases the limitation of the maximal rate of delay variation, and allows delay change rapidly in a derived range. Correspondingly, the LMI controller is derived from the stability condition. Furthermore, using the Matlab LMI Toolbox, the controller gain matrices can be found by solving a set of appropriate linear matrix inequalities. Also, this thesis uses the electromagnetism-like optimization mechanism to find the maximal tolerable delay, which will enhance the performance of the networked controller.
Finally, numerical examples are used to examine the proposed stability analysis and fuzzy controller design and simulated by using MATLAB software. The simulation results verify the correctness and performance of the proposed method.

並列關鍵字

Interval Type-2 T-S Fuzzy Model ； Networked Control Systems (NCS) ； Fast-Varying Delay ； Neural Network ； Lyapunov Functional ； Electromagnetism-Like (EM) Optimization

參考文獻

[45] 康振涵，使用區間型Type-2 T-S模糊理論之智慧型網路控制系統控制器設計，碩士論文，國立台北科技大學電機工程系碩士班，台北，2009。

[38] 謝坤霖，可考慮封包遺失率之網路TS模糊控制器設計，碩士論文，國立台北科技大學電機工程系碩士班，台北，2008。

[4] R. Oboe and P. Fiorini, “A design and control environment for Internet-based telerobotics,” International Journal of Robotics Research, vol. 17, Apr. 1998, pp. 433-449.

[6] G. P. Liu, W. S. Hu and D. Rees, “Design and implementation of networked predictive control systems based on round trip time delay measurement,” Proceedings of the American Control Conference, Jun. 2006, pp. 674-679.

[7] Q. Wang, J. Q. Yi, D. B. Zhao and J. T. Wen, “BP neural network prediction-based variable-period sampling approach for networked control systems,” Applied Mathematics and Computation, vol. 185, no. 2, Feb. 2007, pp. 976-988.