本論文針對一般具有不明確的動態非線性系統，提出具有適應性的模糊滑動控制器，以滑動曲面當作模糊邏輯控制器的輸入並採用直接型的調整法則與間接型的調整法則來調整控制器的後件部參數，來達成系統穩定的目的。同時並使其系統具有強健性與適應性。
大略可以分成以下三點:
1.在降低輸入變數方面，設計以距離型為基礎的模糊輸入類似模糊滑動模態控制器，並基於李阿普若夫穩定性定理來推導出模糊調整律並應用於具有不明確的混沌系統中。所設計的調整法則是針對距離型為基礎的模糊滑動控制器來調整後件部參數，並結合盲區(dead-zone)的特性使得調整法則具有強健性。
2.針對欠驅動四階的非線性系統提出解耦合適應性模糊邏輯控制器，除了近似系統的理想等效控制器外還改善滑動模態控制器中抖動現象。在欠驅動非線性系統方面，引用解耦合方式來處理，藉由兩個子系統滑動模式所建構出一個滑動曲面來當作模糊邏輯控制器輸入，並藉由李阿普若夫來推導出調整律，以調整控制器的後件部參數，並藉由估測方式來推導出抖動控制器的增益大小。同時針對系統動態的性能，以控制命令當作輸入經由模糊推論來調整兩個子系統的滑動向量以求得適當值，進而改善系統的性能。
3.針對多輸入/多輸出的雙軸機械手臂系統來設計兩個單輸入/單輸出的適應性模糊滑動控制器來完成控制目的，所採用方法是以滑動曲面當作模糊邏輯的輸入並以間接式的調整法則來近似系統的未知參數，而系統中的近似誤差或是外來干擾會對追蹤誤差有所影響。所以結合 控制觀念抑制這些干擾，當系統的所有狀態和訊號均是有界時，近似誤差或是外界干擾對追蹤誤差可以被設定到一可接受範圍值內，而達到所期望的性能反應。
以上針對單輸入/單輸出的混沌系統、單輸入/多輸出的欠驅動系統與多輸入/多輸出的機械手臂系統來模擬以說明方法的可行性，並驗證系統的適應性、強健性與穩定性。

This work presents an adaptive fuzzy sliding-mode controller for a class of uncertain nonlinear systems. The controller design deals with handles the problems of the dimensionality of fuzzy input variables in fuzzy logic control, and effectively frees it from the chattering phenomena in sliding-mode control. The designed adaptive fuzzy controller based on sliding-mode has these features. The main results are as follows.
1. An adaptive fuzzy sliding-mode control strategy for a class of chaotic oscillators is presented. This class of chaotic systems includes both externally and parametrically excited systems. The controller can track the states and disturbances of at nonlinear system and construct an adaptive law, even when the exact model of the system is not known. This distance-based adaptive fuzzy sliding-mode control method makes three main contributions to this proposed model-free fuzzy sliding-mode control. First, it removes the trial-and-error process for finding suitable fuzzy rules, thus significantly decreasing the computational effort. Second, the fuzzy adaptation mechanism reduces the effects of parameter variations and disturbances. Considering the existing approaches of handling external disturbances, the proposed approach does not need a bound to be known; only requiring that it exists, and can guarantee that the state trajectory be zero. Finally, this on-line modification rule with dead-zone also improves the stability property, and increasing the speed at which the sliding surface can be reached.
2. A decoupled adaptive fuzzy sliding-mode control design scheme is described, along with a consequence adaptation, for a class of fourth-order nonlinear systems. Every subsystem, which is decoupled into two second-order systems, is said to have a main and a sub-control purpose. Two sliding surfaces are built from the state variables of the decoupled subsystem. The main and sub-target conditions for these sliding surfaces, and an intermediate variable obtained from the sub-sliding surface condition is then introduced. The proposed adaptation law, which results from the direct adaptive approach, is adopted to determine the appropriate center of the unknown system variables. The membership functions in the THEN-part vary according to the width of the adaptation of consequence. If the bound of the estimated error chosen is too large, then the control effort causes significant chattering. If the estimate error bound chosen is too small, the stability of the control system cannot be ensured. The proposed method is robust in the presence of uncertainties and bounded external disturbances. Besides, with the effects on system dynamic performance, both the slope of sliding-mode surface, are automatically tuned by real-time fuzzy inference, respectively.
3. A robust indirect adaptive fuzzy sliding-mode controller for a robotic manipulators is designed. This controller is adopted for a class of multiple-input multiple-output systems with unknown non-linear dynamics. Indeed, it is suggested that an on-line fuzzy adaptation methods can approximate unknown non-linear functions to design the sliding-mode control. An indirect adaptive fuzzy sliding-mode control technique is adopted to attain tracking for a robot manipulator in cases with external disturbances. The proposed methodology combines the attenuation technique, fuzzy logic approximation method, and adaptive control algorithm to generate a robust tracking control design for a robotic manipulator. The adaptive fuzzy approximation technique is adopted as rough tuning while the disturbance attenuation technique is adopted for fine-tuning. With this adaptive fuzzy control algorithm not only assures the stability of the closed-loop, but also maintains the need tracking performance.

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