Title: Multiple parameter estimation using Gram-Schmidt Orthonormalization for brushless DC motor actuators

Authors: Liangtoa Zhu, Ravi Patankar

Addresses: Mechanical Engineering, Michigan Technological University, Houghton, MI 49931, USA. ' Intelligent Automation, Inc., 15400 Calhoun Dr., Suite 400, Rockville, MD 20855, USA

Abstract: An approximate motor inverse model is usually employed to achieve torque control of a brushless DC motor. Variations of motor parameters directly impart inaccuracies in the motor inverse model, thus the performance of the system suffers. A multi-parameter estimation method based on Gram-Schmidt Orthonormalization in a continuous function space of feedback signal is proposed in this paper. The stability of the estimation scheme is proved. Performance improvement of the estimation scheme is discussed. Comparison of simulations for closed loop voltage control of an electric power steering system actuator confirms a lower bound of error of the estimated parameter and faster adaptation with the proposed improvements for the estimation scheme.

Keywords: adaptive estimation; nonlinear systems; motor control; multiple parameter estimation; inverse models; Gram-Schmidt Orthonormalization; brushless DC motors; actuators; simulation; closed loop voltage control; electric power steering; mechatronics.

DOI: 10.1504/IJVAS.2006.009309

International Journal of Vehicle Autonomous Systems, 2006 Vol.4 No.1, pp.88 - 101

Published online: 16 Mar 2006 *

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