輪型行動機器人之多項式模糊控制

近幾年來，由於機器人控制技術已經在各個應用領域中被廣泛的應用，如產品加工、救災…等。而且機器人有以下的優點：對環境的適應力強和不會覺得疲勞。因此機器人的研究就更顯得重要。本文提出利用T-S模糊控制和多項式模糊控制來實現行動機器人的路徑追蹤控制。當多項式模糊控制的狀態矩陣都是常數時，它就可以化簡成T-S模糊控制。此外，衰退率能藉由調整Lyapunov指數來縮短系統的收斂時間。干擾抑制則能夠在系統受到干擾時，將系統受到干擾的影響降到最低。所以作者利用多項式Lyapunov函數推導出平方和型式的衰退率穩定條件和干擾抑制穩定條件。接著，利用Matlab的SOSTOOLS解平方和型式的穩定條件，得到平行分佈補償控制器的控制增益。最後，在電腦模擬提供：對於T-S模糊控制和多項式模糊控制之機器人的路徑追蹤利用基本穩定條件、衰退率穩定條件、干擾抑制穩定條件來設計的控制器。還有展現T-S模糊控制和多項式模糊控制的求解空間，藉此來突顯多項式模糊控制的優點。

關鍵字

多項式模糊控制；平行分佈補償； T-S模糊控制；輪型行動機器人；衰退率；干擾抑制

並列摘要

This thesis is a proposal for the design of polynomial fuzzy controllers with decay rate and disturbance rejection for the path tracking of a wheeled mobile robot (WMR). A polynomial Lyapunov function is used to analyze and derive the stability conditions of the polynomial fuzzy system with decay rate and disturbance rejection because it is more relaxed than a linear matrix inequality (LMI) approach to Takagi-Sugeno (T-S) fuzzy modeling and control. The constraint conditions are represented by the sum of squares (SOS) of the polynomial fuzzy system and can be numerically solved using the recently developed SOSTOOLS. According to the SOS approach, the parallel distributed compensation (PDC) controller is obtained to track the state trajectory of a reference model. Computer simulations are used to show the T-S fuzzy control and polynomial fuzzy control for path tracking of the WMR. Then, we compare the SOS approach with the LMI approach, and it is clear that the SOS approach is more relaxed than the LMI approach.

並列關鍵字

Polynomial fuzzy control ； Parallel distributed compensation ； T-S fuzzy control ； Wheeled mobile robot ； Decay rate ； Disturbance rejection

參考文獻

[1] T. H. Lee, H. K. Lam, F. H. F. Leung, and P. K. S. Tam, “A practical fuzzy logic controller for the path tracking of wheeled mobile robots,” IEEE Control Systems Magazine, vol. 23, no. 2, pp. 60-65, April 2003.

[2] D. Chwa, “Sliding-mode tracking control of nonholonomic wheeled mobile robots in polar coordinates,” IEEE Transactions on Control Systems Technology, vol. 12, no.4, pp. 637-644, July 2004.

[3] B. S. Park, S. J. Yoo, J. B. Park, and Y. H. Choi, “Adaptive neural sliding mode control of nonholonomic wheeled mobile robots with model uncertainty,” IEEE Transactions on Control Systems Technology, vol. 17, no. 1, pp. 207-214, Jan. 2009.

[5] R. Langari and M. Tomizuka, “Analysis and Synthesis of Fuzzy Linguistic control systems,” in Proc. ASME Winter Annual Meet., 1990, pp.35-42.

[7] K. Tanaka and H. O. Wang, “Fuzzy control systems design and analysis: a linear matrix inequality approach,” John Wiley and Sons, Inc, USA, 2001.

國際替代計量

輪型行動機器人之多項式模糊控制

未授權

主題瀏覽