Developing of adaptive model predictive control system for heat treatment of iron-ore pellets with using recursive least square algorithm for online parameter estimation

Authors

DOI:

https://doi.org/10.15587/2312-8372.2016.80596

Keywords:

adaptive model predictive control, heat treatment of iron-ore pellets, online parameter estimation, recursive least square algorithm

Abstract

The article discusses the problems of development of the system of adaptive predictive control of pellets heat treatment with online estimation of parameters of the process model. Due to nonstationarity in time of the process parameters caused by fluctuations of particle size distribution and fractional void of the layer, changes in the process equipment characteristics and the presence of noise in measurement channels, the existing automation systems of pellets heat treatment do not always allow to solve the problem of stabilization temperature profile in the pellets layer, as well as reduce the specific consumption of energy. To overcome these disadvantages the recursive least squares algorithm is proposed to use for estimating the parameters of process model which subsequently is the base for calculating the manipulated variable (the gas flow to the burner of the leading side of the indurating machine) with using the methods of Model Predictive Control theory that provides maintenance of a preset temperature regime of pellets indurating under conditions of uncontrolled disturbances. In accordance with the described approach it is suggested the variant of the structure of the system of adaptive predictive control of the temperature regime of pellets indurating in the separate gas-air chamber of indurating machine, and the simulation of this system was performed in Simulink package with the use of real data about the dependence of temperature in the heart of firing zone from gas consumption on the burner of leading side, which were obtained in a mode of passive experiment at the indurating machine OK-324 of JSC «Central GOK (ME)». The resulting system has demonstrated the high quality of the online estimation of parameters and sufficient convergence rate for conditions of pellets heat treatment. The obtained results allow us to recommend the developed method of formation of adaptive predictive control for automation of pellets heat treatment.

Author Biographies

Sergij Ruban, State Higher Educational Institution «Kryvyi Rih National University», Str. Vladimir Matusevich, 11, Kryvyi Rih, Ukraine, 50000

Candidate of Technical Sciences, Associate Professor

Department of Computer Science, Automation and Control Systems

Vadim Kharlamenko, State Higher Educational Institution «Kryvyi Rih National University», Str. Vladimir Matusevich, 11, Kryvyi Rih, Ukraine, 50000

Candidate of Technical Sciences, Senior Lecturer

Department of Computer Science, Automation and Control Systems

Sergij Tsvirkun, Kryvyi Rih College of National Aviation University, Str. Tupolev, 1, Kryvyi Rih, Ukraine, 50000

Candidate of Technical Sciences, Head of Department

Department of Radio Engineering and Electromechanics

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Published

2016-09-29

How to Cite

Ruban, S., Kharlamenko, V., & Tsvirkun, S. (2016). Developing of adaptive model predictive control system for heat treatment of iron-ore pellets with using recursive least square algorithm for online parameter estimation. Technology Audit and Production Reserves, 5(2(31), 30–34. https://doi.org/10.15587/2312-8372.2016.80596

Issue

Vol. 5 No. 2(31) (2016): Systems and control processes. Information and control systems. Technology Transfer in the Transport Industry

Section

Systems and Control Processes: Original Research

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Copyright (c) 2016 Sergij Tsvirkun, Sergij Ruban, Vadim Kharlamenko

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