A normal form augmentation approach to adaptive control of space robot systems
Dynamics and Control
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Contact Friction Compensation for Robots Using Genetic Learning Algorithms
Journal of Intelligent and Robotic Systems
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In this paper, the kinematics and dynamics of free-floating space robot system with dual-arms are analyzed. The closed-loop dynamic error equation considering uncertainties for the space robot is derived by using the PD type computed torque method. A new learning control method using real coded genetic algorithm is presented to control the system and its controller structure is designed. A compensating learning control item is added to the error equation to approach the uncertainties by evolutionary learning. Then, the computed torque method and the GA learning control are combined to realize the perfect trajectory tracking. Simulation results show the efficiency of the control method.