{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T23:49:58Z","timestamp":1773964198797,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2018,9,28]],"date-time":"2018-09-28T00:00:00Z","timestamp":1538092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>This article presents a novel technique for the fast tuning of the parameters of the proportional\u2013integral\u2013derivative (PID) controller of a second-order heat, ventilation, and air conditioning (HVAC) system. The HVAC systems vary greatly in size, control functions and the amount of consumed energy. The optimal design and power efficiency of an HVAC system depend on how fast the integrated controller, e.g., PID controller, is adapted in the changes of the environmental conditions. In this paper, to achieve high tuning speed, we rely on a fast convergence evolution algorithm, called Big Bang\u2013Big Crunch (BB\u2013BC). The BB\u2013BC algorithm is implemented, along with the PID controller, in an FPGA device, in order to further accelerate of the optimization process. The FPGA-in-the-loop (FIL) technique is used to connect the FPGA board (i.e., the PID and BB\u2013BC subsystems) with the plant (i.e., MATLAB\/Simulink models of HVAC) in order to emulate and evaluate the entire system. The experimental results demonstrate the efficiency of the proposed technique in terms of optimization accuracy and convergence speed compared with other optimization approaches for the tuning of the PID parameters: sw implementation of the BB\u2013BC, genetic algorithm (GA), and particle swarm optimization (PSO).<\/jats:p>","DOI":"10.3390\/a11100146","type":"journal-article","created":{"date-parts":[[2018,10,2]],"date-time":"2018-10-02T08:23:50Z","timestamp":1538468630000},"page":"146","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["Fast Tuning of the PID Controller in An HVAC System Using the Big Bang\u2013Big Crunch Algorithm and FPGA Technology"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8400-3836","authenticated-orcid":false,"given":"Abdoalnasir","family":"Almabrok","sequence":"first","affiliation":[{"name":"Department of Informatics, University of Piraeus, 18534 Piraeus, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5359-619X","authenticated-orcid":false,"given":"Mihalis","family":"Psarakis","sequence":"additional","affiliation":[{"name":"Department of Informatics, University of Piraeus, 18534 Piraeus, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anastasios","family":"Dounis","sequence":"additional","affiliation":[{"name":"Department of Industrial Design and Production Engineering, University of West Attica, 12244 Piraeus, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,9,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1049\/ip-cta:20020103","article-title":"PID Controllers: Recent Tuning Methods and Design to Specification","volume":"149","author":"Cominos","year":"2002","journal-title":"IEEE Proc. 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