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A human wearing an exoskeleton-type assistive device results in a parallel control system that includes two controllers: an exoskeleton controller and a human brain that includes the spinal cord and the cerebrum. Unknown and complicated characteristics of the brain dynamically interact with the exoskeleton controller, which makes the controller design challenging. In this paper, the motion control system of a human is regarded as a feedback control loop that consists of the brain, muscles, and the dynamics of the extended human body. The brain is modeled as a control algorithm amplified by a fictitious gain (FG). The FG is adjusted to compensate for characteristic changes in the muscle and human body dynamics due to physical impairment, varying load, or any other causes. In this paper, an exoskeleton controller that realizes the FG is designed, and its performance and robustness are discussed.