Robust microprocessor control of robot manipulators (Q1088962)

The problem of robust tracking for robot manipulators in the presence of uncertainty and input constraints is studied. Using the theory of uncertain dynamical systems, robust nonlinear control strategies, with guaranteed tracking properties that can be quantified given bounds on the extend of model uncertainty, sensor noise, input disturbances, etc., are derived. A torque optimization strategy is also utilized to optimize the joint torques in the event of actuator saturation. Experimental results are presented here showing the feasibility and performance of the control strategy.