Transaction on Control Automation, and Systems Engineering 2002; 4(4): 330-340
© The International Journal of Control, Automation, and Systems
In this paper, a non-linear approach to a design of model reference adaptive control is presented. The approach is demonstrated by a case study of a simple single-pole and no zero, linear, discrete-time plant. The essence of the idea is to generate a full non-linear model of the plant dynamics and the parameter adaptation dynamics as a gradient descent algorithm with respect to a Riemannian metric. It is shown how a Riemannian metric can be chosen so that the modelled plant dynamics do in fact match the true plant dynamics. The performance of the proposed scheme is compared to a traditional model reference adaptive control scheme using the classical sensitivity derivatives (Euclidean gradients) for the descent algorithm.
Keywords adaptive control, discrete-time system, riemannian geometry
Transaction on Control Automation, and Systems Engineering 2002; 4(4): 330-340
Published online December 1, 2002
Copyright © The International Journal of Control, Automation, and Systems.
Sang-Heon Lee/Robert Mahony/Il-Soo Kim
In this paper, a non-linear approach to a design of model reference adaptive control is presented. The approach is demonstrated by a case study of a simple single-pole and no zero, linear, discrete-time plant. The essence of the idea is to generate a full non-linear model of the plant dynamics and the parameter adaptation dynamics as a gradient descent algorithm with respect to a Riemannian metric. It is shown how a Riemannian metric can be chosen so that the modelled plant dynamics do in fact match the true plant dynamics. The performance of the proposed scheme is compared to a traditional model reference adaptive control scheme using the classical sensitivity derivatives (Euclidean gradients) for the descent algorithm.
Keywords: adaptive control, discrete-time system, riemannian geometry
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