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Optimal control of grinding mill circuit using model predictive static programming: A new nonlinear MPC paradigm

le Roux, Johan D and Padhi, Radhakant and Craig, Ian K (2014) Optimal control of grinding mill circuit using model predictive static programming: A new nonlinear MPC paradigm. In: JOURNAL OF PROCESS CONTROL, 24 (12, SI). pp. 29-40.

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Official URL: http://dx.doi.org/ 10.1016/j.jprocont.2014.10.007

Abstract

The recently developed reference-command tracking version of model predictive static programming (MPSP) is successfully applied to a single-stage closed grinding mill circuit. MPSP is an innovative optimal control technique that combines the philosophies of model predictive control (MPC) and approximate dynamic programming. The performance of the proposed MPSP control technique, which can be viewed as a `new paradigm' under the nonlinear MPC philosophy, is compared to the performance of a standard nonlinear MPC technique applied to the same plant for the same conditions. Results show that the MPSP control technique is more than capable of tracking the desired set-point in the presence of model-plant mismatch, disturbances and measurement noise. The performance of MPSP and nonlinear MPC compare very well, with definite advantages offered by MPSP. The computational speed of MPSP is increased through a sequence of innovations such as the conversion of the dynamic optimization problem to a low-dimensional static optimization problem, the recursive computation of sensitivity matrices and using a closed form expression to update the control. To alleviate the burden on the optimization procedure in standard MPC, the control horizon is normally restricted. However, in the MPSP technique the control horizon is extended to the prediction horizon with a minor increase in the computational time. Furthermore, the MPSP technique generally takes only a couple of iterations to converge, even when input constraints are applied. Therefore, MPSP can be regarded as a potential candidate for online applications of the nonlinear MPC philosophy to real-world industrial process plants. (C) 2014 Elsevier Ltd. All rights reserved.

Item Type: Journal Article
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Additional Information: Copy right for this article belongs to the ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
Keywords: Comminution; Grinding mill; Model predictive control; Model predictive static programming; Optimal control
Department/Centre: Division of Mechanical Sciences > Aerospace Engineering (Formerly, Aeronautical Engineering)
Date Deposited: 24 Feb 2015 05:49
Last Modified: 24 Feb 2015 05:49
URI: http://eprints.iisc.ernet.in/id/eprint/50856

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