An adaptive PID learning control of robot manipulators. (English) Zbl 0973.93011
This paper presents an adaptive PID learning control scheme for a periodic robot motion under uncertainty. This scheme is composed by a fixed/adaptive PID feedback control part and a feedforward input learning scheme implementing the control strategy, i.e., linear PID feedback stabilization and feedforward learning for nonlinear compensation and tracking. It is shown that all the error signals in the learning control system are bounded and the robot motion trajectory converges to the desired one asymptotically. Updating the PID gain via the adaptive learning rules and the feedforward input learning rules, the adaptive PID learning controller outperforms the fixed PID learning controller while simultaneously removes the lower bound gain conditions required by the fixed PID learning controller for stability and convergence of this learning operation. Computer results illustrate the feasibility and effectiveness of the proposed scheme for online learning of periodic robot motion.
Reviewer: S.G.Tzafestas (Athens)
MSC:
| 93B51 | Design techniques (robust design, computer-aided design, etc.) |
| 93C85 | Automated systems (robots, etc.) in control theory |
| 93C40 | Adaptive control/observation systems |
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