Adaptive hybrid impedance control for a 3DOF upper limb rehabilitation robot using hybrid automata

There is a growing need for effective and adaptive robot-assisted rehabilitation platforms for post-stroke patients which can facilitate considerably their sensorimotor control performance, and also ensure safety for the patients. A 3-DOF adaptive robot-assisted rehabilitation platform is proposed in this work which uses at its core a hybrid impedance control framework to track simultaneously both desired force and position trajectory, while regulating the apparent impedance of the robot as seen by the patient to ensure robot-patient compliant motion. To make the system adaptive to the patient recovery process, the impedance characteristic of the patient´s impaired limb is modeled as a parameter of recovery, and is estimated online using a recursive polynomial model estimator. A hybrid automata is then implemented to specify different apparent robot impedances to track the recovery process. Preliminary simulation results showed good response of the proposed framework to the changing patient´s arm impedance profile as well as good trajectory tracking of force and position in task space.