ENHANCEMENT OF CONTROL’S PARAMETER OF DECOUPLED HVAC SYSTEM VIA ADAPTIVE CONTROLLER THROUGH THE SYSTEM IDENTIFICATION TOOL BOX

Authors

  • Seyed Mohammad Attaran Center for Artificial Intelligence & Robotics, Electrical Engineering Faculty, Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia
  • Rubiyah Yusof Universiti Teknologi Malaysia Jalan Semarak 54100, Bangunan-Malaysia Japan International Institute of Technology (MJIIT), Malaysia

DOI:

https://doi.org/10.11113/jt.v76.4108

Keywords:

HVAC system, PID controller, RGA method, decoupling method

Abstract

Heating, Ventilating and Air Conditioning (HVAC) systems have nonlinear character and nature. Current models for control components and the optimization of HVAC system parameters can be linear approximations based on an operating or activation point, or alternatively, highly complex nonlinear estimations. This duality creates problems when the systems are used with real time applications. The two parameters temperature and relative humidity (RH) have a more direct effect in most applications of HVAC systems than the execution. This study’s objective is to implement and simulate an adaptive controller for decoupled bi-linear HVAC systems for the purpose of controlling the temperature and RH in a thermal zone. The contribution of this study is to apply the adaptive controller for the decoupled bi linear HVAC system via relative gain array (RGA). To achieve this objective, we used a system identification toolbox to increase the speed and accuracy of the identification of system dynamics, as was required for simplification and decoupled HVAC systems. The method of decoupling is relative gain array. The results of the simulation show that when compared with a classical PID controller, the adaptive controller performance is superior, owing to the high efficiency with which the steady state set points for temperature and RH are reached.

References

Salehizadeh, M. r., A. Rahimi-Kian, and M. Oloomi-Buygi. 2015. Security-Based Multi-Objective Congestion Management for Emission Reduction in Power System. International Journal of Electrical Power & Energy Systems. 65(0): 124-135.

Wang, W., R. Zmeureanu, and H. Rivard. 2005. Applying Multi-Objective Genetic Algorithms in Green Building Design Optimization. Building and Environment. 40(11): 1512-1525.

Crawley, D. B., J. W. Hand, M. Kummert, and B. T. Griffith. 2008. Contrasting the Capabilities of Building Energy Performance Simulation Programs. Building and Environment. 43(4): 661-673.

Homod, R. Z. 2013. Review on the HVAC System Modeling Types and the Shortcomings of Their Application. Journal of Energy. 2013: 1-10.

Wang, Y. W., W. J. Cai, Y. C. Soh, S. S. Li, L. Lu, and L. Xie. 2004. A Simplified Modeling of Cooling Coils for Control and Optimization of HVAC Systems. Energy Conversion and Management. 45 (18-19): 2915-2930.

Salazar, R., I. López, and A. Rojano. 2008. A Neural Network Model to Predict Temperature and Relative Humidity in a Greenhouse. International Society for Humor Studies. 801: 539-46.

Pei-Hung Chi, Fang-Bor Weng, and S.-H. C. Ay Su. 2006. Numerical Modeling of Proton Exchange Membrane Fuel Cell with Considering Thermal and Relative Humidity Effects on the Cell Performance. Journal of Fuel Cell Science and Technology. 3(3): 292-303.

Kasahara, M., T. Matsuba, Y. Kuzuu, T. Yamazaki, Y. Hashimoto, K. Kamimura, and S. Kurosu. 1999. Design and Tuning of Robust PID Controller for HVAC Systems. ASHRAE Transactions. 105(2): 154-166.

Benitez, J., J. Cassilas, and O. C. Nand. 2003. Fuzzy Control of HVAC Systems Optimized by Genetic Algorithms. Applied Intelligence. 18(155-77)

F. S. Ismail, R. Yusof, M. Khalid, Z. Ibrahim, and H. Selamat. 2012. Performance Evaluation of Self Organizing Genetic Algorithm for Multi-Objective Optimization Problem. ICIC Express Letters. 6(1): 1-7.

Astrom, K. J. and T. Hagglund. 1995. PID Controllers: Theory, Design, and Tuning. USA: Instrument Society of America, research Triangle Park.

American Society of Heating. 2003. Ashrae Handbook: Heating, Ventilating, and Air-Conditioning Applications: Inch-Pound Edition Amer Society of Heating America Society of Heating.

Qing-Gao, W., H. Chang-Chieh, Z. Yong, and B. Qiang. 1999. Multivariable Controller Auto-Tuning with Its Application in HVAC Systems. American Control Conference (ACC). San Diego, CA. 02 Jun-04 Jun 1999. 4353-4357.

Mudi, R. K. and N. R. Pal. 1999. A Robust Self-Tuning Scheme for PI and PD Type Fuzzy Controllers. IEEE Transactions on Fuzzy Systems. 7(1): 2-16.

Brandt, S. G. and G. Shavit.1984. Simulation of the PID Algorithm for Direct Digital Control Application. In: Workshop on HVAC Controls, Modeling and Simulation. Georgia Institute of Technology. 1984.

Ardehali, M. M., K. H. Yae, and T. F. Smith. 1996. Development of Proportional-Sum-Derivative Control Methodology with Applications to a Building HVAC System. Solar Energy. 57(4): 251-60.

Farris, D. and T. McDonald. 1980. Adaptive Optimal Control-an Algorithm for Direct Digital Control. ASHRAE Transactions. 86: 880-93.

Zelikin, M. 2000. Control Theory and Optimization I: Homogeneous Spaces and the Riccati Equation in the Calculus of Variations. Berlin, Germany: Springer-Verlag.

Cao, C., L. Ma, and Y. Xu. 2012. Adaptive Control Theory and Applications. Journal of Control Science and Engineering. 2012: 2.

Astrom, K. and B. Wittenmark. 1989. Adaptive Control Reading. MA: Addison-Wesley Publishing Company,Inc.

Zaheer-uddin, M., R. V. Patel, and S. A. K. Al-Assadi. 1993. Design of Decentralized Robust Controllers for Multizone Space Heating Systems. IEEE Transactions on Control Systems Technology. 1(4): 246-261.

Parvaresh, A., S. M. Ali Mohammadi, and A. Parvaresh. 2012. A New Mathematical Dynamic Model for HVAC System Components Based on Matlab/Simulink. International Journal of Innovative Technology and Exploring Engineering. 1(2): 1-6.

Ardehali, M. M., T. F. Smith, J. M. House, and C. J. Klaassen. 2003. Assessment of Controls-Related Energy-Inefficiency. ASHRAE Transactions. 109: 111–121.

Underwood, D. M. and R. R. Crawford. 1990. Dynamic Nonlinear Modeling of a Hot-Water-to-Air Heat Exchanger for Control Applications. ASHRAE Transactions. 96: 149-55.

Clark, D. R., C. W. Hurley, and C. R. Hill. 1985. Dynamic Models for HVAC System Components. ASHRAE transactions. 91(1): 737-51.

Maxwell, G. M., H. N. Shapiro, and D. G. Westra. 1989. Dynamics and Control of a Chilled Water Coil. ASHRAE Transactions. 95 (1): 1243-55.

Kasahara, M., Y. Kuzuu, Matsuba T, Y. Hashimoto, K. Kamimura, and S. Kurosu. 2000. Stability Analysis and Tuning of PID Controller in Vav Systems. ASHREA Transactions. 106 Part 2: 285-96.

Riederer, P., D. Marchio, J. C. Visier, A. Husaunndee, and R. Lahrech. 2002. Room Thermal Modelling Adapted to the Test of HVAC Control Systems. Energy Building Transactions. 37: 777-790.

Peng, X. and A. Paassen. 1998. State Space Model for Predicting and Controlling the Temperature Response of Indoor Air Zones. Energy Building Transactions. 28: 197-203.

Elmahdy, A. H. and G. P. Mitalas. 1977. Simple Model for Cooling and Dehumidifying Coils for Use in Calculating Energy Requirements for Buildings. ASHRAE Transactions. 83 Part 2: 103–17.

Zaheer-Uddein, M. 1993. Sub-Optimal Controller for a Space Heating System. ASHRAE Transactions. 99 Part 1: 201-208.

Yao-wen, W., C. Wen-ban, L. Shu-jiang, X. Li-hua, and S. Yeng-Chai. 2002. Development of Cooling Coil Model for System Control and Optimization. The 2002 International Conference on Control and Automation. Xiamen, Fujian Province, China. 19 June 2002. 133.

Clarke, J. A. 2011. Energy Simulation in Building Design. Oxford: Butterworth Heinemann.

Stoecker, W. F. 1975. Procedures for Simulating the Performance of Components and Systems for Energy Calculation. 3d ed. New York: ASHRAE.

Braun, J. E.1988. Methodologies for Design and Control of Central Cooling Plants. Ph.D. Thesis. Department of Mechanical Engineering. University of Wisconsin. Madison. 1988.

Rabehl, R. J., J. W. Mitchell, and W. A. Beckman. 1999. Parameter Estimation and the Use of Catalog Data in Modeling Heat Exchangers and Coils. HVAC&R Research. 5 (1): 3-17.

Nassif, N., S. Kajl, and R. Sabourin. 2010. Modélisation Des Composants D’un Système Cvca Existent Vie Col. Interuniversitaire. Franco-Québécois, Canada.

Becker, M., D. Oestreich, H. Hasse, and L. Litz. 1994. Fuzzy Control for Temperature and Humidity in Refrigeration Systems. Proceedings of the Third IEEE Conference on Control Applications. Glasgow. 24-26 August 1994. 1607-1612.

Qi, Q. and S. Deng. 2009. Multivariable Control of Indoor Air Temperature and Humidity in a Direct Expansion (Dx) Air Conditioning (A/C) System. Build Environ. 44: 1659-67.

Rentel-Gomez, C. and M. Velez-Reyes. 2001 of Conference. Decoupled Control of Temperature and Relative Humidity Using a Variable Air Volume HVAC System and Noninteracting Control. In: Proceeding of the IEEE International Conference on Control Applications. 1147-51.

Bourhan, T., M. Tashtoush, M. Molhim, and M. Al-Rousan. 2005. Dynamic Model of an HVAC System for Control Analysis. Energy 30: 1729-1745.

Goodwin, G. C., S. F. Graebe, and M. E. Salgado. 2000. Control System Design. 1st. USA: Prentice Hall.

Salgado, M. E. and A. Conley. 2004. Mimo Interaction Measure and Controller Structure Selection. International Journal of Control. 77(4): 367-383.

Bristol, E. H. 1966. On a New Measure of Interaction for Multivariable Process Control. process control. IEEE Transactions on Automatic Control. 11: 133-134.

Dumont, G. A.2011. Decoupling Control of Mimo Systems. Electrical and Computer Engineering University of British Columbia. 2011.

Chai, T., X. Wang, and H. Yue. 2000. Multivariable Intelligent Decoupling Control and Its Applications. Proceedings of the 3rd World Congress on Intelligent Control and Automation. Hefei. 28 June-02 July 2000. 23-29.

Weihong, H. and Y. Xuejun. 2008. Decoupling Control of a Variable-Air-Volume Air-Conditioning System Based on State Feedback. Second International Symposium on Intelligent Information Technology Application, (IITA). Shanghai,China. 20-22 December 2008. 589-592.

Vaes, D., J. Swevers, and P. Sas. 2004. Optimal Decoupling for Mimo-Controller Design with Robust Performance. Proceedings of the American Control Conference. Boston, MA, USA. 30 June-2 July 2004. 4601-4606.

Sanda, F. F. 2005. Decoupling in Distillation. Journal of Control Engineering and Applied Informatics. 7(1): 10-19.

Wang, H., G. P. Liu, C. J. Harris, and M. Brown. 1995. Advanced Adaptive Control. Pergamon: Press.

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Published

2015-08-27

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Section

Science and Engineering

How to Cite

ENHANCEMENT OF CONTROL’S PARAMETER OF DECOUPLED HVAC SYSTEM VIA ADAPTIVE CONTROLLER THROUGH THE SYSTEM IDENTIFICATION TOOL BOX. (2015). Jurnal Teknologi (Sciences & Engineering), 76(1). https://doi.org/10.11113/jt.v76.4108