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Conventional and decentralized PID controllers applied to a multivariable aerothermic process

By Mustapha Ramzi, LASTIMI Laboratory (University Mohammed V of Rabat)

In the industrial processes, the interaction between the main variables is generally considered as challenging for mono-variable controllers. In fact, for industrial systems strongly coupled, a change in any of these variables can have a significant impact on other variables. To reduce the effect of this coupling, several techniques have been used in the literature [1,2]. In this paper, the static decoupler approach is used to reduce the interaction between the main variables of a multivariable aerothermic process [3]. It is a pilot scale heating and ventilation system [4]. An abrupt change in the ventilator speed might cause an undesirable disturbance in the air temperature representing a factor that must be managed to conserve energy. The comparison between conventional and decentralized PID controllers applied to a multivariable aerothermic process is presented. To demonstrate the effectiveness of these methods, an implementation is performed on the Xcos of Scilab software. The control parameter syntheses are obtained by using the continuous state space model [3,5]. The identification of a multivariable model is based on the experimental data. The outcome of the experimental results is that the main control objectives, such as set-point tracking and interactions rejection are well achieved. The simulation results have shown that the proposed method provides a significant improvement compared to the conventional PID controller.


Static decoupler, PID controller, decentralized PID controller, Xcos, Scilab.

[1] H. Garnier, M. Gilson, T. Bastogne, and M. Mensler, “CONTSID toolbox: a software support for continuous-time data-based modelling. In Identification of continuous time models from sampled data”, H.Garnier and L. Wang (Eds.), Springer, London, 2008, pp. 249-290. 
[2] Dale E. Seborg, Thomas F. Edgard, Duncan A. Mellichamp, “Process dynamics and control”, Second edition, John Wiley & sons, 2004 , pp. 473-502.
[3] M. Ramzi and H. Youlal, Continuous Time Identification and Decentralized PID Controller of an Aerothermic Process, International journal on smart sensing and intelligent systems, Vol. 5, N°. 2, June 2012.
[4] Manual for ERD004000 Flow and Temperature process, 78990 ELANCOURT, FRANCE, 2008. 
[5] T. Nguyen L. Vu and M. Lee “Independent design of multi-loop PI/PID controllers for interacting multivariable processes”, Journal of Process Control 20, 2010, pp. 922–933.