CONTRIBUTION TO THE INDIRECT DECENTRALIZED ADAPTIVE-CONTROL OF MANIPULATION ROBOTS

In this paper, efficient approaches to the synthesis of indirect decen tralized adaptive control for manipulation robots are presented. The f irst part of control synthesis consists of the estimation of unknown d ynamic robot parameters using the methods of recursive identification and fast dynamic as well as identification models in a symbolic form. The second part of synthesis includes the self-tuning control strategy which is a basis for adaptive control synthesis according to the esti mates of the unknown dynamic parameters. Using the theory of decentral ized systems, a new robust algorithm for adaptive control with the abi lity of adaptation in the feedforward or feedback loop are proposed. A complete stability and convergence analysis is presented. A special p art of the paper represents an analysis of practical implementation of the proposed control algorithms on modern microprocessor-based robot controllers. Based on this analysis, an efficient application of indir ect adaptive algorithms in real time with high-quality system performa nce is shown. Adaptive algorithms are verified through simulation of t rajectory tracking for an industrial robot with unknown dynamic parame ters of payload.