Title :
Repetitive learning control: a Lyapunov-based approach
Author :
Dixon, W.E. ; Zergeroglu, E. ; Dawson, D.M. ; Costic, B.T.
Author_Institution :
Robotics & Process Syst. Div., Oak Ridge Nat. Lab., TN, USA
fDate :
8/1/2002 12:00:00 AM
Abstract :
In this paper, a learning-based feedforward term is developed to solve a general control problem in the presence of unknown nonlinear dynamics with a known period. Since the learning-based feedforward term is generated from a straightforward Lyapunov-like stability analysis, the control designer can utilize other Lyapunov-based design techniques to develop hybrid control schemes that utilize learning-based feedforward terms to compensate for periodic dynamics and other Lyapunov-based approaches (e.g., adaptive-based feedforward terms) to compensate for nonperiodic dynamics. To illustrate this point, a hybrid adaptive/learning control scheme is utilized to achieve global asymptotic link position tracking for a robot manipulator
Keywords :
Lyapunov methods; adaptive control; compensation; feedforward; learning (artificial intelligence); manipulators; stability; Lyapunov-based approach; Lyapunov-like stability analysis; control design; global asymptotic link position tracking; hybrid adaptive learning control; learning-based feedforward term; nonperiodic dynamics; periodic dynamics; repetitive learning control; robot manipulator; unknown nonlinear dynamics; Hybrid power systems; Laboratories; Manipulator dynamics; Programmable control; Robotic assembly; Robust control; Service robots; Stability analysis; US Department of Energy; Vehicle dynamics;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2002.1018772