On one hand, the lower extremity exoskeleton is a wearable robotic device that can enable a human to walk with heavy load for a prolonged period of time without reducing the human’s agility [1]. On the other hand, because of fast growing of aging population in so many countries in the world this also is used for the elderly and muscle disease patient rehabilitation. In this research, kinematics, inverse kinematics and the dynamic model of the exoskeleton have been analyzed. The tracking issue and solving uncertainty problems play important roles in controlling the exoskeleton system. Therefore, two control methods, impedance control and adaptive fuzzy control are used to demonstrate the tracking performance of the exoskeleton. Matlab software is used to construct a mathematical model, a 1-DOF model and a 3-DOF model of the exoskeleton and verify the workability of those two control methods. Real input data of target trajectory is filtered to eliminate the disturbances in order to enhance the performance. Comparisons between those two control methods and other methods are described. Adaptive fuzzy controllers are capable of adapting the mass changes of the system. A proposed idea of implementation is also mentioned in the conclusions and future work session.

On one hand, the lower extremity exoskeleton is a wearable robotic device that can enable a human to walk with heavy load for a prolonged period of time without reducing the human’s agility [1]. On the other hand, because of fast growing of aging population in so many countries in the world this also is used for the elderly and muscle disease patient rehabilitation. In this research, kinematics, inverse kinematics and the dynamic model of the exoskeleton have been analyzed. The tracking issue and solving uncertainty problems play important roles in controlling the exoskeleton system. Therefore, two control methods, impedance control and adaptive fuzzy control are used to demonstrate the tracking performance of the exoskeleton. Matlab software is used to construct a mathematical model, a 1-DOF model and a 3-DOF model of the exoskeleton and verify the workability of those two control methods. Real input data of target trajectory is filtered to eliminate the disturbances in order to enhance the performance. Comparisons between those two control methods and other methods are described. Adaptive fuzzy controllers are capable of adapting the mass changes of the system. A proposed idea of implementation is also mentioned in the conclusions and future work session.

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