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Architecture & Urban Research Institute

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³í¹®¸í °¡º¯¼Ó ³Ãµ¿½Ã½ºÅÛÀÇ Á¤¹Ð ¿Âµµ Á¦¾î¸¦ À§ÇÑ ´ÙÀÔ¡¤Ãâ·Â ¸ðµ¨¿¹Ãø Á¦¾î±â ¼³°è / Design of Multiple Input-Multiple Output Model Predictive Controller for Precise Temperature Control of Variable Speed Refrigeration System
ÀúÀÚ¸í À±¹Î±â(Min Gi Yoon) ; Á¤¼®±Ç(Seok Kwon Jeong)
¹ßÇà»ç ´ëÇѼ³ºñ°øÇÐȸ
¼ö·Ï»çÇ× ¼³ºñ°øÇÐ³í¹®Áý, Vol.36 No.04 (2024-04)
ÆäÀÌÁö ½ÃÀÛÆäÀÌÁö(161) ÃÑÆäÀÌÁö(14)
ISSN 1229-6422
ÁÖÁ¦ºÐ·ù ȯ°æ¹×¼³ºñ
ÁÖÁ¦¾î ¸ðµ¨¿¹Ãø Á¦¾î; ´ÙÀÔ?Ãâ·Â; ¿ÀÀÏÄð·¯ ½Ã½ºÅÛ; °¡º¯¼Ó ³Ãµ¿½Ã½ºÅÛ ; Model predictive control; Multi-input multi-output; Oil cooler system; Variable speed refrigeration system
¿ä¾à1 º» ¿¬±¸¿¡¼­´Â VSRS ±â¹Ý ¿ÀÀÏÄð·¯ ½Ã½ºÅÛÀÇ °­ÀÎÇϰí Á¤¹ÐÇÑ ¿Âµµ Á¦¾î¸¦ À§ÇØ MPC¸¦ ¼³°èÇÏ¿´´Ù. ÁÖ¿ä ¼³°è ÆÄ¶ó¹ÌÅÍÀÎ ¿¹Ãø Ãâ·Â ¼ö ¿Í ¿¹Ãø ÀÔ·Â ¼ö ¸¦ ¿ÀÀÏÃⱸ¿Âµµ ÀÇ °úµµ Ư¼ºÀ» ºÐ¼®ÇÏ¿© ÀûÀýÇÑ °ªÀ¸·Î ¼±Á¤ÇÏ¿´´Ù. ¼³°èµÈ MPC´Â Á¶ÀÛ±âÀÇ ¹°¸®Àû Á¦¾àÁ¶°Ç ÇÏ¿¡¼­ ¿¹Ãø ÃßÁ¾ ¿ÀÂ÷¿Í Á¦¾îÀÔ·Â º¯È­·®À¸·Î ÀÌ·ç¾îÁø ¸ñÀûÇÔ¼ö¸¦ ÃÖ¼ÒÈ­ÇÏ¿© ÃÖÀûÀÇ Á¦¾îÀÔ·ÂÀ» µµÃâÇÏ¿´´Ù. Áö·É°ª º¯°æ ¹× ¿­ºÎÇÏ Áõ?°¨ ½Ã¹Ä·¹ÀÌ¼Ç ¹× ½ÇÇè °á°ú, MPC´Â ¿ÀÀÏÃⱸ¿Âµµ ¸¦ ¾ö¹ÐÇÏ°Ô Á¦¾îÇÏ¿´À¸¸ç, ÀιöÅÍ Á֯ļö ÀÇ °£¼· ¿µÇâÀ» ¿¹ÃøÇÏ¿© °ú¿­µµ ÀÇ ¿ÀÂ÷¸¦ ÃÖ¼ÒÈ­ÇÏ´Â EEV °³µµ Áö·É ¸¦ Àΰ¡ÇÏ¿´´Ù. ÃÖÁ¾ÀûÀ¸·Î Dual SISO ±â¹Ý PI Á¦¾î±â¿ÍÀÇ Á¦¾î¼º´É ºñ±³¸¦ ÅëÇØ ¼³°èÇÑ MPCÀÇ À¯È¿¼ºÀ» È®ÀÎÇÏ¿´´Ù. º» ¿¬±¸ÀÇ ÁÖ¿ä °á·ÐÀ» ¿ä¾àÇÏ¸é ´ÙÀ½°ú °°´Ù.


(1) MPC´Â ¿ÀÀÏÃⱸ¿Âµµ ¸¦ ¸ñÇ¥ ¿Âµµ¿¡ ¾ö¹ÐÈ÷ ÃßÁ¾½ÃÄ×°í, ½ºÅÜ »óÀÇ ¿Ü¶õ Àΰ¡¿¡ ´ëÇØ¼­µµ Çã¿ë ¿ÀÂ÷ ¹üÀ§ ¡¾0.1¡É À̳»ÀÇ °­ÀÎÇÑ ¿Âµµ Á¦¾î¸¦ ½ÇÇöÇÏ¿´´Ù.
(2) MPC ¼³°è ½Ã ¿¹Ãø Ãâ·Â ¼ö ´Â ½Ã½ºÅÛÀÇ ¹Ì·¡ »óÅ ¿¹ÃøÀ» À§ÇØ ÀûÀýÇÏ°Ô Å« °ªÀ», ¿¹Ãø ÀÔ·Â ¼ö ´Â Á¦¾î±âÀÇ °úµµÇÑ °è»ê ºÎ´ãÀ» ÁÙÀ̱â À§ÇØ ÀûÀýÇÏ°Ô ÀÛÀº °ªÀ» ¼±Á¤ÇØ¾ß ÇÑ´Ù.
(3) ¸ñÀûÇÔ¼öÀÇ ¿¹Ãø ¿ÀÂ÷ ¿¡ ºÎ°¡µÈ °¨¼è Çà·Ä Àº ¿Âµµ °èÃø ¼¾¼­ÀÇ ¿­ÀâÀ½À¸·Î ÀÎÇÑ °úµµÇÑ ¿¹Ãø Ãâ·ÂÀ» ¸·°í, Á¦¾î¼º´ÉÀÇ ¿­È­¸¦ ¹æÁöÇÏ´Â µ¥ ±â¿©ÇÏ¿´´Ù.
(4) MPC´Â ¿¹Ãø ¹æÁ¤½ÄÀ» ÅëÇØ °£¼· ¿µÇâÀ» ¿¹ÃøÇÏ¿© Á¦¾îÇϹǷΠDual SISO ±â¹Ý PI Á¦¾î±â¿ÍÀÇ ºñ±³¿¡¼­ ¿Í ¸¦ ¸ðµÎ ´õ ºü¸£°í Á¤¹ÐÇÏ°Ô Á¦¾îÇÏ¿´´Ù.
¿ä¾à2 Variable speed refrigeration systems are composed of multiple input multiple output systems with several state variables. These input/output variables and state variables typically have various constraints, making it challenging to design optimal control considering these constraints. However, model predictive control (MPC) has been gaining attention in process control recently due to its ability to optimally control a multi-input multi-output system with a number of constraints and early constraints reflection. It can predict future outputs while taking into account current constraints through quadratic programming optimization with a mathematical algorithm. Subsequently, it can determine the optimal control input. To verify the validity of MPC, the control performance of MPC was compared with conventional PI control satisfying constraints through Matlab simulation and experiment on the oil cooler system.
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DOI https://doi.org/10.6110/KJACR.2024.36.4.161