This paper proposes a model-free robust-adaptive controller for Euler-Lagrange systems with a quantitative performance analysis in terms of state-errors. The controller has only few parameters, and the procedure of finding the controller parameters is intuitive and easy to implement. The controller acts as an adaptive computed-torque controller and consists of two feedback loops: the inner loop evaluates the robot dynamics to linearize the system and the outer loop is a simple proportional derivative controller. Input-to-state stability is used to derive the control law and tune the controller parameters. Inverse-optimal control using the Hamilton-Jacobi-Isaacs equations is utilized to confirm the optimality of the controller. Robustness of the proposed controller is proved using the H ∞ optimality technique. The controller starts with zero system information and adapts itself to the real system dynamics. Finally, the proposed technique is validated on a three-degree-of-freedom and a seven-degree-of-freedom robot manipulator.
Robust-adaptive controller design for robot manipulators using the H∞ approach
2019-05-17
Article (Journal)
Electronic Resource
English
Polynomial-Based Robust Adaptive Tracking Control of Robot Manipulators
British Library Online Contents | 1998
|A Hybrid Controller of Adaptive and Learning Control for Robot Manipulators
British Library Online Contents | 2006
|A Decentralized Fuzzy Controller for Robot Manipulators
British Library Conference Proceedings | 1993
|Design of adaptive sliding mode controller for manipulators using neural networks
British Library Online Contents | 1997
|Adaptive sliding mode controller with time-varying switching surfaces for robot manipulators
British Library Online Contents | 1997
|