Date of Award

12-1991

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Michael B. Leahy, Jr., PhD

Abstract

Principal Base Parameter Analysis (PBPA) is a general and systematic procedure for determining the dynamic parameters that directly contribute to the joint torques of a manipulator, ranked in order of sensitivity. The feasibility of employing PBPA as an aid in the design and tuning of adaptive model-based controllers for industrial manipulators is rigorously investigated. This is accomplished by employing PBPA to determine the minimal size of the adaptive parameter vector and more importantly, to develop a less heuristic procedure for controller tuning. A simple, step-by-step procedure is developed wherein the manipulator torque equations are used in conjunction with PBPA to develop a functional adaptive model-based control (AMBC) algorithm, then tune the algorithm for optimal performance. Experimental analysis contrasts this adaptive model-based controller, designed and tuned using PBPA, to the completely heuristic procedure employed in previous Air Force Institute of Technology research. The incorporation of PBPA into the AMBC design methodology reduces the time and expertise necessary to tune the controller for satisfactory tracking performance.

AFIT Designator

AFIT-GE-ENG-91D-48

DTIC Accession Number

ADA243833

Comments

The author's Vita page is omitted.

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