Autocovariance-based plant-model mismatch estimation for linear model predictive control

by Wang, S; Simkoff, JM; Baldea, M; Chiang, LH; Castillo, I; Bindlish, R; Stanley, DB

Journal of Systems & Control Letters; Jun 2017; Volume 104; Pages: 5-14;  DOI: 10.1016/j.sysconle.2017.03.002

In this paper, we present autocovariance-based estimation as a novel methodology for determining plant-model mismatch for multiple-input, multiple-output systems operating under model predictive control. Considering discrete-time, linear time invariant systems under reasonable assumptions, we derive explicit expressions of the autocovariances of the system inputs and outputs as functions of the plant-model mismatch. We then formulate the mismatch estimation problem as a global optimization aimed at minimizing the discrepancy between the theoretical autocovariance estimates and the corresponding values computed from historical closed-loop operating data. Practical considerations related to implementing these ideas are discussed, and the results are illustrated with a chemical process case study.

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