4.5 Article

Optimum control of under-grate pressure of clinker cooler by optimizing the proportional integral derivative controller parameters using honey badger algorithm technique

期刊

OPTIMAL CONTROL APPLICATIONS & METHODS
卷 44, 期 5, 页码 2938-2959

出版社

WILEY
DOI: 10.1002/oca.3018

关键词

clinker cooler; gain parameters; honey badger algorithm; pressure of cooler; proportional-integral-differential (PID) controller

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This article proposes an optimization approach for a PID controller using the honey badger algorithm to control the under-grate pressure of a clinker cooler. The proposed approach provides optimum cooling rate, lower electricity consumption, and stable temperature compared to existing techniques.
The minimum air pressure necessary at the grate to penetrate a bed of heated clinker of a certain thickness and permeability is known as under-grate pressure. It is vital to keep the under-grate pressure consistent because excessive pressure causes the clinker to form an unstable suspension and minimum pressure allows heat from the clinker to harm the cooler grates. So it is necessary to obtain excellent performance through reasonable control methods. For this purpose, this article proposes an optimization approach for a proportional integral derivative (PID) controller to control the pressure below the grate of the clinker cooler. The proposed optimization approach is the honey badger algorithm (HBA), which mimics the feeding habits of honey badgers. The main aim of proposed approach is to maintain and regulate under-grate pressure of clinker cooler using HBA and provide optimum cooling rate to clinker. The proposed approach based grate cooler also provide the less electricity consumption and stable temperature. The proposed technique is implemented in MATLAB and its efficiency is compared to various existing techniques. From the simulation, the electricity consumption of proposed approach RMSE is 158 and mean accuracy is 98.65. Under-grate pressure based RMSE is 5.01 and the mean accuracy become 99.55. The outlet temperature based RMSE of proposed approach is 4.32 and mean accuracy is 81.21. These values are lower than existing approaches, it reveals the proposed approach is better than the existing one.

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