کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
689020 889585 2014 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Optimal control of grinding mill circuit using model predictive static programming: A new nonlinear MPC paradigm
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی تکنولوژی و شیمی فرآیندی
پیش نمایش صفحه اول مقاله
Optimal control of grinding mill circuit using model predictive static programming: A new nonlinear MPC paradigm
چکیده انگلیسی


• Model predictive static programming (MPSP) is applied to a grinding mill circuit.
• MPSP performance is compared with nonlinear model predictive control (NMPC).
• Improved output regulation and reduced computational cost is achieved with MPSP.
• MPSP requires only a few iterations to converge even when input constraints apply.
• MPSP shows potential for online application in industrial process plants.

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Process Control - Volume 24, Issue 12, December 2014, Pages 29–40
نویسندگان
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