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Adaptive Robot Manipulators In Global Technology

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Conference

2009 Annual Conference & Exposition

Location

Austin, Texas

Publication Date

June 14, 2009

Start Date

June 14, 2009

End Date

June 17, 2009

ISSN

2153-5965

Conference Session

Develop Course / Materials / Topics for a Global Engineering Education

Tagged Division

International

Page Count

6

Page Numbers

14.161.1 - 14.161.6

Permanent URL

https://peer.asee.org/4563

Download Count

14

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Paper Authors

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Alireza Rahrooh University of Central Florida

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Alireza Rahrooh is aProfessor of Electrical Engineering Technology at the University of Central Florida. He received the B.S., M.S., and Ph.D. degrees in Electrical Engineering from the Univ. of Akron, in 1979, 1986, and 1990, respectively. His research interests include digital simulation, nonlinear dynamics, chaos, control theory, system identification and adaptive control. He is a member of ASEE, IEEE, Eta Kappa Nu, and Tau Beta Pi.

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Scott Shepard University of Central Florida

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Scott Shepard is an Assistant Professor of Electrical Engineering Technology -- Photonics, at the University of Central Florida. He received a B.S. in Electrical Engineering and a B.S. in Physics from Kansas State University in 1979; and a M.S., and Ph.D. in Electrical Engineering from the Massachusettes Institute of Technology, in 1981 and 1992 respectively. From 1980 to 1986 he was a Member of the Technical Staff at Bell Laboratories. His research interests currently include quantum optics, nonlinear dynamics, communication and control system performance assessment and refinement, solar energy, and optical sensors.

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Walter Buchanan Texas A&M University

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Walter W. Buchanan is J.R. Thompson Chair Professor and Department Head of Engineering Technology and Industrial Distribution at Texas A&M University. He received his BSE and MSE from Purdue University, and his Ph.D. and J.D. from Indiana University. Walt is a P.E. in six states and is Past Chair of ETC and past member of the Executive Committee of TAC of ABET. He has written over 100 papers and is a member of the Board of Directors of NSPE.

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Adaptive Robot Manipulators in Global Technology

Abstract

Model-based feedback control algorithms for robot manipulators require the on-line evaluation of robot dynamics and are particularly sensitive to modeling inaccuracies. This paper presents an adaptive technique for practical implementation of model-based robot control strategies and introduces a novel adaptive algorithm which makes the design insensitive to modeling errors. The design incorporates an on-line identification technique to eliminate parameter errors and individual joint controllers to compensate for modeling inaccuracies. An illustrated example is given to demonstrate the development of the proposed algorithm through a simple two- dimensional manipulator. New applications for robot manipulators are continually being discovered with global impacts due to integration of computer controlled robots.

I. Introduction

The continuously increasing demands for enhanced productivity and improved precision have imposed special requirements on the control of industrial robots and caused a shift of emphasis towards the dynamic behavior of manipulators. This shift has led to the development of model- based control algorithms which incorporate the dynamic model of the manipulator in the control law in order to decouple the robot joints. The underlying principle is to: (1) design a nonlinear feedback algorithm that will effectively linearize the dynamic behavior of the robot joints; and (2) synthesize linear controllers to specify the closed-loop response.

The critical assumption in model-based control is that the robot dynamics are modeled accurately based upon precise knowledge of the kinematic and dynamic parameters of the manipulator. Unfortunately, this assumption is not always practical. Inevitable modeling and parameter errors may degrade controller performance and even lead to instability. Modeling errors are introduced by unmodeled dynamics or simplified models that are designed to reduce the real-time computational requirements of the controller. Parameter errors arise from practical limitations in the specification of numerical values for the kinematic and dynamic robot parameters or from payload variations.

The objective of this paper is to introduce an adaptive design to improve the performance of robot manipulators. The proposed design augments the model-based robot controller with an adaptive identifier of robot dynamics to reduce parameter errors. The identifier estimates the dynamic parameters of the manipulator from measurements of the inputs and outputs (joint positions, velocities, and accelerations) and calibrates adaptively the model in the controller.

II. Problem Statement

The matrix-vector formulation of the closed-form dynamic model for a robot with N joint axes1 is: && & D(q, λ) q + h ( q, q, λ) = F(t) (1)

Rahrooh, A., & Shepard, S., & Buchanan, W. (2009, June), Adaptive Robot Manipulators In Global Technology Paper presented at 2009 Annual Conference & Exposition, Austin, Texas. https://peer.asee.org/4563

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