Sistem Kontrol Prediktif Nonlinier Berbasis Fuzzy Pada HVAC

Widhiastutii, Putri Ayu (2008) Sistem Kontrol Prediktif Nonlinier Berbasis Fuzzy Pada HVAC. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kontrol prediktif merupokan jenis dari advanced Kontrol yang memberikan dampak significant terhadap perkembangan sistem kontrol di industri. Perkembangan kontrol prediktif linier dengan penggunaan model yang non linier memberilcan hasil yang kurang memuaskan sehingga dibutuhkan pengembangan metode kontrol nonlinier yang mampu menjawah terhatlap peruhahan kondisi yang terjadi. Kontrol prediktif menggunakan internal model sistem untuk memprediksi perilaku masa depan sistem mulai saat ini sampai kondisi yang ditentukan. Sehingga mutlak diperlukan model yang mampu merepresentasikam proses yang ditinjau. Kemampuan fuzy dalam memetakan hubungan nonlinier antara input-output dimanfaatkan dalam pengembangan algoritma koontrol prediktif Metode ini diimplementasikan pada plant HVAC. yang memiliki perilaku sistem yang nonlinier. Dengan hasil pemodelan fuzzy clustering didapatkam validasi 99.575% dan nilai RMSE sebesar 0.17864. Sistem kontrol prediktif nonlinier yang dikembangkan mampu menghasilkan performansi sistem yang haik, sistem stabil pada semua set point yang diberikan Untuk perubahan gangguan lemperatur set point naik. diperoleh lag time sebesar 25 detik, setling time sebesar 350 detik, dengan offset sebesar 0.919 % (0.386 °C). Sedangkan untuk peruhahan gangguan set point turun diperoleh lag time sebesar 25 detik, dengan setling time sebesar 325 detik, dan qffset sebesar 0.31% (0.124 °C)
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Predictive control is a type of advanced control that has a significant impact on the development of control systems in industry. The development of linear predictive control with the use of nonlinear models provides unsatisfactory results so that it is necessary to develop nonlinear control methods that are able to respond to changes in conditions that occur. Predictive control uses an internal system model to predict the future behavior of the system from now until the specified conditions. So it is absolutely necessary to have a model that is able to represent the process being reviewed. Fuzzy's ability to map nonlinear relationships between inputs and outputs is utilized in the development of predictive control algorithms. This method is implemented in an HVAC plant. which has nonlinear system behavior. With the results of fuzzy clustering modeling, 99.575% validation and an RMSE value of 0.17864 are obtained. The developed nonlinear predictive control system is able to produce good system performance, the system is stable at all given set points. For changes in temperature disturbances, the set point increases. The resulting lag time is 25 seconds, the settling time is 350 seconds, and the offset is 0.919% (0.386 °C). Meanwhile, for the downward set point disturbance, the resulting lag time is 25 seconds, the settling time is 325 seconds, and the offset is 0.31% (0.124 °C)

Item Type:	Thesis (Other)
Additional Information:	RSF 629.8 Put s-1 2008 (weeding)
Uncontrolled Keywords:	Sistem kontrol, Prediktif, identifikasi , Fuzzy modelling, HVAC; Control systems, Predictive, identification, Fuzzy modeling, HVAC
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ213 Automatic control.
Divisions:	Faculty of Industrial Technology > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User:	EKO BUDI RAHARJO
Date Deposited:	05 Jan 2026 02:05
Last Modified:	05 Jan 2026 02:05
URI:	http://repository.its.ac.id/id/eprint/129234

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