Output Feedback Adaptive Trajectory Tracking Control For Flexible-joint Robot Manipulators

In comparison to the traditional robot manipulators with both rigid joints and rigid links,flexible-joint robot manipulators featured with compact structure,light weight and low-energy consumption,are commonly used in the industry.In this thesis,output feedback adaptive trajectory tracking control for flexible-joint robot manipulators is investigated by singularly perturbation theory and integral concept,and the research results will provide theoretical support for their practical application of high performance.Firstly,according to the simplified model of flexible joint by Spong,dynamics model of flexible-joint robot manipulators is obtained by using the Lagrange equation.Then,the singularly perturbation theory and integral concept are applied to decouple the dynamics into a slow subsystem and a fast subsystem,where the slow subsystem indicates the rigid part of the flexible-joint manipulator,and the fast one is to describe the flexible joint.Thus,the controller design issue for the flexible-joint robot manipulators can be transformed into two independent sub-controllers design for the subsystems.Secondly,considering parametric uncertainties in the dynamics model and external disturbances with unknown upper bound,a robust adaptive control scheme in an improved linear parameterization expression is designed for the slow subsystem.On the other side,by deforming the expression of the fast subsystem,the control objective is changed into a typical tracking issue,which makes the controller design for fast subsystem more flexible.In addition,an approximate differential filter is applied in both slow and fast subsystems to eliminate the velocity measurements completely for both links and joint motors,so as to achieve OFT control with only position measurements.Thirdly,a bounded adaptive control approach is proposed for flexible-joint robot manipulators with parametric uncertainties and bounded torque inputs.In the controller design,a class of saturation functions is used to make the control law bounded,ensuring the torque control inputs within the output limitation of the joint actuators.An adaptive control law of projection type is adopted to handle the feed-forward term of the slow sub-controller with parametric uncertainties.Meanwhile,a linear filter and a high-gain observer are utilized in the slow and fast subsystems,respectively,to estimate the unmeasurable states,making the complete closed-loop control with only position measurements of both links and joint motors.Importantly,a corrective control scheme is proposed according to the singular perturbation theory and integral concept,to realize the flexibility compensation for strong flexibility system,which makes the singular perturbation theory also feasible for the robot manipulators with strong joint flexibility.Finally,with respect to the stability analysis for the flexible-joint robot manipulators,considering the stability of the slow and fast subsystems cannot directly guarantee the stability of the whole composite system,we give two stability analysis methods for the whole singular perturbation system.In addition,simulations are implemented to test and verify the effectiveness of the proposed controllers,comparative results show that the robust adaptive output feedback controller and the bounded adaptive output feedback controller proposed in this thesis have better trajectory tracking performance.