English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

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

PID2018 Benchmark Challenge:Multi-Objective Stochastic Optimization Algorithm