Robust control of redundant manipulators with constraints using a general reduced order model

Redundant manipulators can achieve additional objectives in conjunction with the main task of tracking the desired end-effector trajectory. When these additional objectives are expressed in the form of motion constraints, control algorithms can be developed to satisfy both the main and additional tasks simultaneously without explicit computation of the inverse kinematics. The paper considers the problem of controller design for redundant robots in the presence of uncertainties in the dynamic model. It is proposed that a simple and effective solution to this problem can be obtained by: first using a reduction procedure to obtain a lower dimensional system which retains the structure property of the original system; second based on the theory of guaranteed stability of uncertain systems, controlling the reduced system in such a way that the complete system is driven to the goal configuration.