The LIMPACT is an exoskeleton developed to be used in identifying the reflex properties of the arm in stroke survivors. Information on joint reflexes helps in designing optimal patient specific therapy programs. The LIMPACT is dynamically transparent by combining a lightweight skeleton with high power to weight ratio actuators. The LIMPACT is supported by a passive weight balancing mechanism to compensate for the weight of the exoskeleton and the human arm. Various self-aligning mechanisms allow the human joint axes to align with the axes of the exoskeleton which ensure safety and short don/doff times. The torque controlled motors have a maximum torque bandwidth of 97 Hz which is required for fast torque perturbations and smooth zero impedance control. The LIMPACT's weight is reduced five times as gravitational forces are lowered using a model-based gravity compensation algorithm. The impedance controller ensures tracking of a cycloidal joint angle reference. A cycloid with an amplitude of 1.3 rad and a maximum velocity of 6.5 rad/s has a maximum tracking error of only 7%. The LIMPACT fulfills the requirements to be used in future diagnostics measurements for stroke patients.
Robotics used for diagnostic measurements on, e.g. stroke survivors, require actuators that are both stiff and compliant. Stiffness is required for identification purposes, and compliance to compensate for the robots dynamics, so that the subject can move freely while using the robot. A hydraulic actuator can act as a position (stiff) or a torque (compliant) actuator. The drawback of a hydraulic actuator is that it behaves nonlinear. This article examines two methods for controlling a nonlinear hydraulic actuator. The first method that is often applied uses an elastic element (i.e. spring) connected in series with the hydraulic actuator so that the torque can be measured as the deflection of the spring. This torque measurement is used for proportional integral control. The second method of control uses the inverse of the model of the actuator as a linearizing controller. Both methods are compared using simulation results. The controller designed for the series elastic hydraulic actuator is faster to implement, but only shows good performance for the working range for which the controller is designed due to the systems nonlinear behavior. The elastic element is a limiting factor when designing a position controller due to its low torsional stiffness. The model-based controller linearizes the nonlinear system and shows good performance when used for torque and position control. Implementing the model-based controller does require building and validating of the detailed model.
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