本論文提出三種整合式回授線性化控制器之設計法並應用於汽車主動式懸吊系統。首先，針對於單輸入單輸出非線性系統，設計整合回授線性化與模糊控制之整合式控制器。其中，回授線性化控制器能確保追蹤誤差均勻終極有界的同時，並可將雜訊幾乎消除；一旦進入預期之收斂半徑內，此時模糊控制器可提高追蹤誤差之收斂速度。這部份之成效以四分之一車模型主動式懸吊系統之模擬結果展現之。接著，針對多輸入多輸出非線性系統，一方面設計整合式模糊回授線性化控制器，並應用至全車模型主動式懸吊系統；另一方面，設計整合類神經網路及回授線性化之控制器，並同時應用到半車模型與全車模型之主動式懸吊系統中。三種整合式回授線性化控制器之收斂性，均由李亞普諾夫穩定性理論推導證明之。最後，電腦模擬結果驗證所提出整合式回授線性化控制器，均可有效地改善四分之一車模型、半車模型和全車模型主動式懸吊系統的乘客舒適性。

This dissertation proposes three kinds of integrated feedback linearization controllers for automobile active suspension systems. Firstly, the feedback linearization approach and fuzzy logic control are integrated to design the desired controller for a class of single-input single-output nonlinear system. The feedback linearization control guarantees the almost disturbance decoupling performance and the uniform ultimate bounded stability of the tracking error system. Once the tracking errors are driven to touch the global final attractor with the desired radius, the fuzzy logic control is immediately applied to improve the convergence rate. Simulation results show the effectiveness of this part for a quarter car model of active suspension system. Secondly, the integrated fuzzy feedback linearization controller is developed for a class of multi-input multi-output nonlinear systems and applied to the full car model of active suspension system. Thirdly, an integrated feedback linearization and neural network control is presented for both half and full car models of active suspension systems, respectively. The stability properties of three integrated feedback linearization controllers are guaranteed by adopting the Lyapunov stability theorem. Finally, the simulation results demonstrate that the proposed integrated feedback linearization controller can improve the ride comfort of passenger for quarter car, half car and full car active suspension systems, respectively.

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