以適應性模糊類神經網路設計改良式順滑模態控制

Design of Improved Sliding Mode Control by Adaptive Fuzzy Neural Networks

張書華(Su-Hua Chang)

指導教授 ： 吳明川

國立臺北科技大學/機電學院/機電整合研究所/碩士(2014年)

摘要

本研究針對對一類多輸入多輸出(Multi-Input/Multi-Output, MIMO)具不確定系統與雜訊之非線性系統，提出一種具有改進切換的順滑模態控制(Sliding Mode Control, SMC)的方法。首先使用模糊邏輯系統來預估未知函數的上界。為了降低切跳現象的影響，使用適應性正比積分(Proportional Integral, PI)來取代符號函數。再來，使用類神經網路(Neural Networks, NN)來調整歸屬函數。最後，基於里亞普諾夫穩定分析來設計出適應性追蹤控制法則並應用於質量-彈簧-阻尼-系統來驗證可行性。

關鍵字

順滑模態控制 ； 非線性系統 ； 里亞普諾夫演算法。

並列摘要

For a class of Multi-Input/Multi-Output (MIMO) nonlinear systems with uncertainties and disturbances, this study proposes a chattering-improved sliding mode control (SMC) method. First, a fuzzy logic system is used to estimate the upper bound of the unknown functions. Secondly, we use an adaptive proportional integral (PI) term to replace the sign function in order to reduce the effect of chattering phenomena. Moreover, we use neural networks (NN) to adjust the membership functions. Finally, based on the Lyapunov stability, we design the adaptive tracking control laws and apply them to the mass-spring-damper system to verify the feasibility.

並列關鍵字

Sliding Mode Control ； Nonlinear systems ； Lyapunov algorithm

參考文獻

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