Non-linear predictive GMV control

Tools

Grimble, M.J. and Majeckie, P.; (2008) Non-linear predictive GMV control. In: American Control Conference, 2008. IEEE, USA, pp. 1190-1195. ISBN 9781424420780 (http://dx.doi.org/10.1109/ACC.2008.4586654)

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Abstract

A nonlinear predictive generalized minimum variance (NPGMV) control algorithm is introduced for the control of nonlinear multivariable systems. The plant model is represented by a series combination of a nonlinear operator, which is assumed finite-gain stable, and a linear state-space model, which can include time delays and unstable modes. The main contribution is to incorporate predictive action into the recently introduced Nonlinear GMV controller by defining a multi-step cost index and using a minimum-variance form of the usual GPC cost function. The solution is very different to traditional nonlinear model predictive control, providing a solution which is similar to fixed model based controllers. This does not provide the same constrained optimization features but it does give a controller which is very simple to implement.

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