採用參數相依李雅普諾夫函數(parameter dependent Lyapunov (multiple Lyapunov, non-quadratic Lyapunov) function P˙¹), 因該函數牽涉微分問題至今未完全解決, 本研究計畫將結合時變系統Anderson-Moore 最佳化定理的結果, 尋找非二次穩定之寬鬆條件。所得之寬鬆條件將適用於連續之模糊系統。此外, 基於多項式理論最新研究成果–平方和(SOS), 本研究計畫將不採用線性矩陣不等式(LMI) 法, 而以平方和(SOS) 法研究模糊系統穩定性問題。初步成果顯示平方和 (SOS) 較寬鬆且可應用的範圍較多。所得之寬鬆條件將適用於連續及離散之模糊系統。最後, 藉由文獻上的例子說明提出方法的可行性及實用性。 ; Deduced from robust stability of linear parameter varying (LPV) systems and characterized by parameter-dependent LMI formulations in terms of firing strength belonging to the unit simplex, stability/stabilization conditions involving ¹˙ are investigated. Second, based on recent results on Sum of Squares (SOS) to polynomial matrices, we, without using LMI toolbox, solve LMIs using SOSTOOLS, showing that SOS techniques provide less conservative results. The example shows that our approach utilizing SOSTOOLS provides more relaxation than the traditional LMI solver in MATLAB toolbox. ; 研究期間 9808 ~ 9907
