Application of adaptive multivariable Generalized Predictive Control to a HVAC system in real time

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This paper presents the application of a Multivariable Generalized Predictive Controller (MGPC) for simultaneous temperature and humidity control in a Heating, Ventilating and Air- Conditioning (HVAC) system. The multivariable controlled process dynamics is modeled using a set of MISO models on-line identified from measured input-output process data. The controller synthesis is based on direct optimization of selected quadratic cost function with respect to amplitude and rate input constraints. Efficacy of the proposed adaptive MGPC algorithm is experimentally demonstrated on a laboratory-scale model of HVAC system. To control the airconditioning part of system the designed multivariable predictive controller is considered in a cascade dual-rate control scheme with PID auxiliary controllers.

[1] F. BEN AICHA, F. BOUANI and M. KSOURI: A multivariable multiobjective predictive controller. Int. J. of Applied Mathematics and Computer Science, 23(1), (2013), 35-45.

[2] O. BEGO, N. PERIC and I. PETROVIC: Decoupling multivariable GPC with reference observation. In 10th Mediterranean Electrotechnical Conf., 2 (2000), 819-822, [3] Y. CHEN and Z. CHEN: A neural-network-based experimental technique for determining Z-transfer function coefficients of a building envelope. Building and Environment, 35(3), (2000), 181-189.

[4] C.-M. CHOW, T.-W. YOON and D.W. CLARKE: An approach to multivariable predictive control with stability guarantees. In UKACC Int. Conf. on Control’96, 2, (1996), 1350-1355.

[5] E. FEKI, M. AYMEN ZERMANI and A. MAMI: Decoupling control approach for neonate incubator system. Int. J. of Computer Applications, 47(2), (2012), 49-57.

[6] H.J. FERREAU: qpOASES user’s manual., 2012.

[7] M. GULAN, M. SALAJ and B. ROHAL’-ILKIV: Real-time implementation of an adaptive feedback and feedforward generalized predictive controller. In Proc. of the 19th Int. Conf. on Process Control, ˇ Strbsk´e Pleso, Slovakia, (2013), 383-388.

[8] M. KÁ RNÝ , A. HALOUSKOV´A and J. B¨OHM: Mimo - a set of SISO? Multivariate system adaptively controlled as a set of single-input single-output models. In IFAC Workshop MICC ’92., Prague, Czech Republic, (1992).

[9] R. KULHAVÝ and M. K´ARN´Y: Tracking of slowly varying parameters by directional forgetting. In Proc. of the 9th IFAC World Congress, Budapest, Hungary, 10 (1984), 78-83.

[10] R. KULHAV´Y and M.B. ZARROP: On a general concept of forgetting. Int. J. of Control, 58(4), (1993), 905-924.

[11] E.P. LAMBERT: Process control applications of long-range prediction. Ph.D. dissertation, University of Oxford, 1987.

[12] C. MOHTADI, D.W. CLARKE and P.S. TUFFS: Generalized predictive control - part I. The basic algorithm. Automatica, 23(2), (1987), 137-148.

[13] N. NASSIF, S. KAJL and R. SABOURIN: Evolutionary algorithms for multiobjective optimization in HVAC system control strategy. In IEEE Annual Meeting of the North American Fuzzy Information Processing Society - NAFIPS, 2004., 1 (2004), 51-56.

[14] J.E. NORMEY-RICO and E.F. CAMACHO: Multivariable generalised predictive controller based on the smith predictor. IEE Proceedings - Control Theory and Applications, 147(5), (2000), 538-546.

[15] C. ÖZSOY: Self-tuning control of a heating, ventilating and air-conditioning system. In Proc. of the Institution of Mechanical Engineers, Part I: J. of Systems and Control Engineering, 207 (1993), 243-251.

[16] J.A. ROSSITER: Model-Based Predictive Control: A Practical Approach. CRC Press, Boca Raton, 2003.

[17] D. SOLOWAY, J. SHI and A. KELKAR: GPC-based stable reconfigurable control. NASA/TP-2004-212823, (2004).

[18] G. TAKÁCS and B. ROHAL’-ILKIV: Model Predictive Vibration Control: Efficient Constrained MPC Vibration Control for Lightly Damped Mechanical Structures. Springer-Verlag, London, 2012.

[19] Q.-G. WANG, C.-C. HANG, Y. ZHANG and Q. BI: Multivariable controller autotuning with its application in HVAC systems. In Proc. of the American Control Conference, 1999, San Diego, California, USA, 6 (1999), 4353-4357.

Archives of Control Sciences

The Journal of Polish Academy of Sciences

Journal Information

IMPACT FACTOR 2016: 0.705

CiteScore 2016: 3.11

SCImago Journal Rank (SJR) 2016: 0.231
Source Normalized Impact per Paper (SNIP) 2016: 0.565


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