Abstract
Serving Stewart plat as wheel-legged construction, the most outstanding superiority of proposed wheel-legged hybrid robot (WLHR) is active vibration isolation during rolling on rugged terrain. This paper presents a force-driven control approach based on model predictive control (MPC) to design optimal control input for Stewart parallel wheel-leg that locomotes using swing foot trajectory. Adding adaptive impedance control in outermost loop, controlling framework prevents robot body horizontal and from vibration over rolling motion. Through dynamic model of Stewart mechanism, controller first creates predictive model by combining Newton-Euler equation, Newton-Raphson iteration of forward kinematic solving for current configuration, inverse kinematic calculation of Stewart obtaining desired joint position, and Gain/Integration module determining reference torque. With minimizing control deviation and input as objective function, a novel control optimization formulation generates optimum input for each control duration. These actuating force naturally enables each strut stretching and retracting used to realize six degree-of-freedom (6DOF) motion for Stewart wheel-leg. We exploit the variable-adapting method to reasonably adjust environmental impedance parameters by current position, velocity, force feedback of wheel-leg. This allow us to adequately acknowledge the desired support force tracking, isolating robot from isolation that is generated from unknown terrain. We demonstrate the validation of our control methodology on physical prototype by tracking a Bezier curve and active vibration isolation while the robot is rolling on decelerate strip. Respectively given PI controller and a sort of traditional impedance controller as comparison, a better performance of proposed algorithm was operated and evaluated through displacement and force sensors internally-installed in each cylinder, as well as IMU mounted on robot body.
Active Vibration Isolation Using a Voice Coil Actuator with Absolute Velocity Feedback Control