Intelligent self-tuning controllers for robot manipulators

Abstract

The design problem of an intelligent self-tuning controller, characterized by a two-layer hierarchical structure, is addressed. The layers are organized according to their functions and goals. The control level is implemented as a self-tuning adaptive controller, where a variety of control laws and identification methods exist as candidates for the controller and identification portions, respectively. Integration of a controller-estimator pair is carried out according to the guidelines provided by the coordination level. The organization level, implemented as a Petri network, supervises the control level, serves as an interface between the user and the system, and resolves several issues which arise from the coordination process between the two layers