Self-tuning prediction and control for two-dimensional processes part 1: fixed parameter algorithms

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Self-tuning prediction and control for two-dimensional processes part 1: fixed parameter algorithms. / Heath, W.P.; Wellstead, P.E.
In: International Journal of Control, Vol. 62, No. 1, 01.1995, p. 65-107.

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Heath WP, Wellstead PE. Self-tuning prediction and control for two-dimensional processes part 1: fixed parameter algorithms. International Journal of Control. 1995 Jan;62(1):65-107. doi: 10.1080/00207179508921534

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Heath, W.P. ; Wellstead, P.E. / Self-tuning prediction and control for two-dimensional processes part 1: fixed parameter algorithms. In: International Journal of Control. 1995 ; Vol. 62, No. 1. pp. 65-107.

RIS

TY - JOUR

T1 - Self-tuning prediction and control for two-dimensional processes part 1: fixed parameter algorithms

AU - Heath, W.P.

AU - Wellstead, P.E.

PY - 1995/1

Y1 - 1995/1

N2 - Least-squares optimal prediction, minimum variance control and generalized minimum variance control algorithms for a two-dimensional CARMA process are developed. Each algorithm involves the algebraic solution of a two-dimensional diophantine equation, and may be embedded within ‘classical’ two-dimensional systems theory. We show how the algorithms must be modified for any practical implementation to take into account the edges of the data field. In this case we show how we may analyse the process using multivariable theory, and explore the linkages between multivariable representations and two-dimensional systems.

AB - Least-squares optimal prediction, minimum variance control and generalized minimum variance control algorithms for a two-dimensional CARMA process are developed. Each algorithm involves the algebraic solution of a two-dimensional diophantine equation, and may be embedded within ‘classical’ two-dimensional systems theory. We show how the algorithms must be modified for any practical implementation to take into account the edges of the data field. In this case we show how we may analyse the process using multivariable theory, and explore the linkages between multivariable representations and two-dimensional systems.

U2 - 10.1080/00207179508921534

DO - 10.1080/00207179508921534

M3 - Erthygl

VL - 62

SP - 65

EP - 107

JO - International Journal of Control

JF - International Journal of Control

IS - 1

ER -