區間二型模糊控制系統的LMI強健穩定條件

本論文研究目的是在考慮系統有外部干擾與模式不確定性的情況下，利用區間二型T-S模糊模型來建構受控體，並且提出四個區間二型T-S模糊控制系統的LMI穩定條件。其中因為區間二型T-S模糊模型具有處理模式不確定性的能力，因此區間二型T-S模糊模型比傳統T-S模糊模型更近似於真實世界中的受控體。本論文提出新的區間二型T-S模糊控制系統的LMI穩定條件，來確保所設計的區間二型模糊控制器對於具有外部干擾和模式不確定性的非線性控制系統是全域穩定。本論文藉由Lyapunov函數推導出基於LMI的強健穩定性條件，並可以利用Matlab LMI Toolbox來求解出適當的控制增益。經由實驗結果，說明利用所推導的基於LMI之強健穩定性條件去設計模糊控制器，不但可以有更好的性能，而且穩定條件更寬鬆和一般性，具更大的解空間。

關鍵字

模式不確定性；外部干擾；區間二型T-S模糊控制系統；強健控制

並列摘要

In this thesis, an interval Type-2 Takagi-Sugeno fuzzy logic control system (IT2 T-S FLCS) with model uncertainty and external disturbance was investigated; the control systems consisted of an IT2 T-S fuzzy model and IT2 fuzzy controllers. The IT2 T-S fuzzy model has greater capability to simulate a plant, compared with the traditional T-S fuzzy model. This thesis presents new theorems that can be used to design IT2 fuzzy controllers, and it demonstrates that a nonlinear system with model uncertainty and external disturbance can be globally asymptotically stabilized using these controllers. Four linear matrix inequality based (LMI-based) stability conditions for the IT2 T-S FLCS are presented. LMI-based robust stability conditions are inferred from the Lyapunov function, which can be numerically solved using the Matlab LMI Toolbox. The results of simulations are provided to illustrate the following: First, fuzzy controllers designed using the proposed theorems have greater capability to deal with model uncertainties. Second, the stability conditions proposed are more general and relaxed compared with existing LMI-based approaches. Finally, the feasible area is greater compared with that in the traditional LMI-based approach.

並列關鍵字

External disturbance ； Interval Type-2 T-S fuzzy logic control systems (IT2 T-S FLCSs) ； Model uncertainty ； Robust control

參考文獻

[1]A. Ghelli, H. Hagras, and J. Dooley, “Towards realizing an intelligent and energy efficient hob by employing a fuzzy logic based embedded agent approach,” in Proc. FUZZ-IEEE, Hyderabad, India, Jul. 2013, pp. 7-10.

[2]N. Altin, “Single phase grid interactive PV system with MPPT capability based on type-2 fuzzy logic systems,” in Proc. IEEE ICRERA, Nagasaki, Japan, Nov. 2012, pp. 1–6.

[3]A. Chakraborty, A. Konar, U. K. Chakraborty, and A. Chatterjee,“ Emotion recognition from facial expressions and its control using fuzzy logic,” IEEE Trans. Syst., Man, Cybern. A, Syst., Humans, vol. 39, no. 4, pp. 726 - 743, Jul. 2009.

[4]N.N. Karnik, J.M. Mendel, “Introduction to type-2 fuzzy logic systems,” in Proc. FUZZ-IEEE, Anchorage, AK, May 1998, pp. 915–920.

[5]Q. Liang and J.M. Mendel, “Interval type-2 fuzzy logic systems: theory and design,” IEEE Trans. Fuzzy Syst., vol. 8, no. 5, pp 535-550, Oct. 2000.

國際替代計量

區間二型模糊控制系統的LMI強健穩定條件

未授權

主題瀏覽