本研究提出一多輸入多輸出非線性系統的控制方法。此方法為多輸入多輸出非線性系統之簡化式模糊自適應解耦合控制。在多輸入多輸出系統中我們主要研究的是系統耦合的效應。此耦合問題可以被當作是一多輸入多輸出系統的各子系統中存在的干擾。因此，在相關研究上一種模糊自適應魯棒控制以 控制來解決此問題。儘管此方法有很好的控制效果，魯棒控制會使控制輸入變得很大。在我們所使用的5自由度外骨骼復健機器人控制系統上，這樣的現象是不好的。我們提出的方法，透過模糊自適應控制去模型化此耦合效應來達成解耦合控制。然而，當我們考慮所有可能的模糊規則，則此規則數量會相當大且學習過程會變的效果不好。因此我們提出一簡化型自適應控制。將多輸入多輸出控制分成多個多輸入單輸出子系統。在模擬上很清楚的證明我們所提出的方法比相關研究提出的方法更好。此外我們也在實際的外骨骼復健系統上使用提出的控制方法。控制結果證明此研究提出的控制方法非常有效。

In this study, a novel design approach is proposed for controlling multi-input multi-output (MIMO) nonlinear systems. This approach is referred to as reduced indirect adaptive fuzzy decoupling control. A main concern for MIMO systems is coupling effects. The coupling problem can be regarded as disturbance existing in all subsystems of a MIMO system. Thus, in the literature, an adaptive fuzzy robust control scheme was proposed to resolve this problem by considering tracking control. Even though that approach indeed can have good robust control performance, due to the robust control nature, sometimes, the control input may be very large. In our practical application, such a dramatic change is not allowable. Our control system is a 5-DOF lower limb exoskeleton rehabilitation robot. In our approach, an adaptive fuzzy control scheme is employed to model those coupling effects. However, if all possible fuzzy rules are considered for coupling terms, the number of rules may become very large and the learning process may become inefficient. Since the adaptive fuzzy system can learn to approximate any uncertainties, in this study, a reduced adaptive control scheme is proposed. The proposed approach is to divide the MIMO system considered into many MISO systems. From our simulations, it is clearly evident that the proposed approach can have much better performance than those proposed in the literature. We also employed the proposed control scheme to an actual lower limb exoskeleton rehabilitation robot and the results confirm the effectiveness of the proposed approach.

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