Disturbance preview and on-line optimization to improve system performance
by
D.O. Philbrick, Z. Jarvis-Wloszak, M.A. Kaya, A.K. Packard and G.J. Balas
in
IEEE Transactions on Automatic Control, vol. 49, no. 2, pp. 266, 2004.
Category: Journal Article
Keywords: Anytime, disturbance preview, model predictive control,
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Abstract:
We present a intuitive and self-contained formulation of a stability preserving receding horizon control strategy for a system where limited preview information is available for the disturbances. The simplicity of the derivation is due to (and its benefits somewhat offset by)a set of stringent and highly structured assumptions. The formulation uses a suboptimal value function for terminal cost, and relies on optimization strategies that only require a trivial improvement property, allowing implementation as an “anytime” algorithm. The nature of this strategy’s performance is clarified with linear examples.
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