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arXiv · 1806.00958

PID2018 Benchmark Challenge:Multi-Objective Stochastic Optimization Algorithm

Abdullah Ates·Jie Yuan·Sina Dehghan·Yang Zhao·Celaleddin Yeroglu·YangQuan Chen
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Abstract

This paper presents a multi-objective stochastic optimization method for tuning of the controller parameters of Refrigeration Systems based on Vapour Compression. Stochastic Multi Parameter Divergence Optimization (SMDO) algorithm is modified for minimization of the Multi Objective function for optimization process. System control performance is improved by tuning of the PI controller parameters according to discrete time model of the refrigeration system with multi objective function by adding conditional integral structure that is preferred to reduce the steady state error of the system. Simulations are compared with existing results via many graphical and numerical solutions.

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Abdullah Ates, Jie Yuan, Sina Dehghan, Yang Zhao, Celaleddin Yeroglu, YangQuan Chen. 2018-06-04. PID2018 Benchmark Challenge:Multi-Objective Stochastic Optimization Algorithm. https://arxiv.org/abs/1806.00958

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