在汽車工業發展中，主動式懸吊系統之設計是用來提供車輛更佳之駕駛操控性與乘座舒適性。因為主動式懸吊系統具有非線性時變之特性，所以要針對其動態特性建立精確之系統數學模式，以做為控制器設計是不容易的，因此本研究利用函數近似法來替代真正之系統數學模式，並結合適應性滑動模式模糊控制方法以補償其誤差，以設計車輛主動式懸吊系統之控制器。其中函數近似法被用來代表系統動態模式中之未知函數，以去除滑動模式控制需要系統數學模式之限制，另外加入具即時自調能力之模糊控制補償器來進行有限項函數近似誤差之補償，改善控制效果及減少實際控制系統實現之困難度。研究中利用Lyapunov 穩定法則來確保控制系統受控過程之穩定性，並藉以獲得系統控制參數之更新律。本研究所提出之控制方法除了藉由電腦模擬之進行，並實際應用於一座1/4車油壓致動主動式懸動系統，透過實驗之結果來驗證其控制效果，並將控制結果與未加入模糊控制補償之控制結果，及利用鑑定所得之系統數學模式所設計之滑動模式控制器來進行比較，以進一步呈現本研究所提出之適應性滑動模式控制器加入模糊控制補償器對於車輛操控性與舒適度之控制成效。

Active suspension systems are designed to provide better ride comfort and handling capability in the automotive industry. Since the active suspension system has nonlinear and time-varying characteristics, it is difficult to establish an accurate dynamic model for designing a model-based controller. Here, a model-free functional approximation based adaptive sliding controller with fuzzy compensation is proposed for an active suspension system. The functional approximation technique is employed to represent the unknown functions, which releases the model-based requirement of the sliding mode control. In addition, a fuzzy scheme with online learning ability is employed to compensate for the modeling error of the functional approximation with finite number of terms for reducing the implementation difficulty. To guarantee the control system stability, the update laws of the coefficients of the approximation function and the fuzzy tuning parameters are derived from the Lyapunov theorem. The proposed controller is implemented on a quarter-car hydraulic actuating active suspension system test rig to investigate the control performance. To verify the dynamic performance improvement of inducing a fuzzy compensation in this model-free controller, the simulation and experimental dynamic responses of the proposed controller are compared with those of the adaptive sliding controller without fuzzy compensation and those of the model-based sliding mode controller.

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