Based On Backstepping Dissipative Control Of Uncertainty Robot Systems

Dissipative control plays an important role for the stability of nonlinear systems, H_∞ control and passivity control are the special examples of it. Because robotic systems are a typical nonlinear system, so dissipative is applied widely in robotic systems. It is known that robot system is a control object with complex nonlinear, strong coupling and lots of uncertainties, and when the manipulator end-effector contacts with the environment, the different environment stiffness affect greatly the system performance. Hence, the research of these two aspects has a special meaning to the control of the robotic system. Aims at these two situations, using dissipative theory and based on backstepping method, this dissertation provides H_∞ robust control,position passivity control and hybrid force/position passivity control. H_∞ control is based on the principle of restraining disturbance. Insuring the systems' stable, H_∞ control makes systems disturbance have a demanded lowest influence to outputs. Based on H_∞ theory and considering the relationship of parameters uncertainty and the outer disturbance, this paper brings forward two control methods, one is that control the parameters uncertainty and the outer disturbance respectively; the other is regards the parameters uncertainty as a part of the outer disturbance, by combining the backstepping method and H_∞ control theory, it avoids the calculation of HJI equation in controlling nonlinear systems using H_∞ method, simplifies the calculation course of the controller and the required controller has a simply structure. Passivity theory primarily analyzes stability of nonlinear systems. The stable result is obtained from the stable character of passivity systems. Using backstepping and the strict-feedback method, aims at different workspaces, this dissertation provides a position passivity control and a hybrid force/position control methods. Decoupling theory and matrix transformation are used in the later method, and the robotic systems is divided into two subsystems, the force control subsystem and the position control subsystem, then to control them respectively, the error of the system can be neglect and the system is stable.