本文提出一改良式細菌演算法，利用改良式細菌演算法調整模糊系統的設計參數並應用於模糊控制系統。由於傳統細菌演算法具複雜操作導致時間複雜度較高，因此改良傳統細菌演算法藉由減低時間複雜度以增加其運算效能，其中改良包括群體反應修正；修正群體相對位置至最佳菌源位置、細菌游動能力調整；細菌游動長度彈性化、細菌同心圓移動模式；幫助細菌跳脫區域最佳解並提升搜尋效能、細菌定位；最佳個體細菌位置保留與菌種調整率；最佳細菌源演化，在此五方面改良傳統細菌規則並估計成本函數調整模糊系統參數達到快速收斂效果。為了即時控制接著設計倒階控制搭配所提之改良式細菌模糊系統，藉由李亞普諾夫函數分析系統穩定性，其中以改良式細菌演算法的成本函數作為閉迴路系統之評估穩定性機制。改良式細菌模糊演化系統包括模糊理論與改良式細菌演算法之結合，故增加控制的穩定及減少演算法運算時間成本，以達到在更好控制效能下並兼具更低的時間複雜度順利實現於實際應用上，最後即時與非即時模擬實驗與實際實驗結果皆展現良好追蹤成效與演算法效能。

This thesis proposes a modified bacterial foraging algorithm to adjust the design of fuzzy systems. Since traditional bacterial foraging algorithms require complicated operations and extremely time-consuming, the modified bacterial foraging algorithm utilize some simplified procedures to reduce the computation time and increase the operation efficiency. The simplified procedures include five parts that include: 1) modified Swarm Behavior, 2) electrification bacterium hover ability, 3) modified bacterium location, 4) adjustment of bacteria source, and 5) the best bacterium source evolution mechanism.
The modified bacterial foraging algorithm is applied to update the parameters of fuzzy systems that approximate nonlinear functions, and to on-line tune the parameters of fuzzy controllers. The DC servo motor experiment and simulation results demonstrate the feasibility and applicability of the proposed methods.

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