TY - GEN
T1 - A passivity-based regressor-free adaptive controller for robot manipulators with combined regressor/parameter estimation
AU - Ebeigbe, Donald
AU - Simon, Dan
N1 - Funding Information:
This research was supported by National Science Foundation Grant 1344954 and a Cleveland State University Graduate Student Research Award.
Publisher Copyright:
Copyright © 2018 ASME
PY - 2018
Y1 - 2018
N2 - This paper develops a new function approximation technique (FAT)-based adaptive controller for the control of rigid robots called the adaptive passivity function approximation technique (APFAT) controller. This controller utilizes the passivity-based approach and simplifies the FAT controller design by eliminating the need for simultaneous estimation of the robot’s inertia matrix, Coriolis matrix, and gravity vector. The controller achieves its simplicity by treating the product of the regressor matrix and parameter vector as an unknown time-varying function to be approximated. The controller can be implemented in robots where the dynamic equations of motion are unknown. The stability of the controller is verified with Lyapunov functions by taking advantage of the passivity property of the robot dynamics. Simulation results on a three degree-of-freedom (DOF) PUMA500 robot demonstrate the ability to track reference trajectories using reasonable control signals when the inertia matrix, Coriolis matrix, and gravity vector are unavailable.
AB - This paper develops a new function approximation technique (FAT)-based adaptive controller for the control of rigid robots called the adaptive passivity function approximation technique (APFAT) controller. This controller utilizes the passivity-based approach and simplifies the FAT controller design by eliminating the need for simultaneous estimation of the robot’s inertia matrix, Coriolis matrix, and gravity vector. The controller achieves its simplicity by treating the product of the regressor matrix and parameter vector as an unknown time-varying function to be approximated. The controller can be implemented in robots where the dynamic equations of motion are unknown. The stability of the controller is verified with Lyapunov functions by taking advantage of the passivity property of the robot dynamics. Simulation results on a three degree-of-freedom (DOF) PUMA500 robot demonstrate the ability to track reference trajectories using reasonable control signals when the inertia matrix, Coriolis matrix, and gravity vector are unavailable.
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U2 - 10.1115/DSCC2018-9010
DO - 10.1115/DSCC2018-9010
M3 - Conference contribution
AN - SCOPUS:85057315549
T3 - ASME 2018 Dynamic Systems and Control Conference, DSCC 2018
BT - Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2018 Dynamic Systems and Control Conference, DSCC 2018
Y2 - 30 September 2018 through 3 October 2018
ER -