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An ANOVA Based Analytical Dynamic Matrix Controller Tuning Procedure for FOPDT Models | ||
| AUT Journal of Modeling and Simulation | ||
| مقاله 8، دوره 42، شماره 2، خرداد 2010، صفحه 55-64 اصل مقاله (682.64 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/miscj.2010.212 | ||
| نویسندگان | ||
| Peyman Bagheri؛ Ali Khaki-Sedigh | ||
| چکیده | ||
| Dynamic Matrix Control (DMC) is a widely used model predictive controller (MPC) in industrial plants. The successful implementation of DMC in practical applications requires a proper tuning of the controller. The available tuning procedures are mainly based on experience and empirical results. This paper develops an analytical tool for DMC tuning. It is based on the application of Analysis of Variance (ANOVA) and nonlinear regression analysis for First Order plus Dead Time (FOPDT) process models. It leads to a simple formula which involves the model parameters. The proposed method is validated via simulations as well as experimental results. A nonlinear pH neutralization model is used for the simulation studied. It is further implemented on a laboratory scale control level plant. A robustness analysis is performed based on the simulation results. Finally, comparison results are provided to show the effectiveness of the proposed methodology. | ||
| کلیدواژهها | ||
| Dynamic Matrix Control؛ Tuning؛ Analysis of Variance (ANOVA)؛ Nonlinear Regression؛ FOPDT؛ industrial processes؛ pH process؛ Level process | ||
| عنوان مقاله [English] | ||
| An ANOVA Based Analytical Dynamic Matrix Controller Tuning Procedure for FOPDT Models | ||
| چکیده [English] | ||
| Dynamic Matrix Control (DMC) is a widely used model predictive controller (MPC) in industrial plants. The successful implementation of DMC in practical applications requires a proper tuning of the controller. The available tuning procedures are mainly based on experience and empirical results. This paper develops an analytical tool for DMC tuning. It is based on the application of Analysis of Variance (ANOVA) and nonlinear regression analysis for First Order plus Dead Time (FOPDT) process models. It leads to a simple formula which involves the model parameters. The proposed method is validated via simulations as well as experimental results. A nonlinear pH neutralization model is used for the simulation studied. It is further implemented on a laboratory scale control level plant. A robustness analysis is performed based on the simulation results. Finally, comparison results are provided to show the effectiveness of the proposed methodology. | ||
| کلیدواژهها [English] | ||
| Dynamic Matrix Control, Tuning, Analysis of Variance (ANOVA), Nonlinear Regression, FOPDT, industrial processes, pH process, Level process | ||
| مراجع | ||
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[1] SJ. Qin and TA, Badgwell, "A survey of industrial model predictive control technology," Control engineering practice, vol. 11, pp. 733-764, 2003. [2] C. R. Cutler and B. L. Ramaker, "Dynamic Matrix Control: A Computer Control Algorithm," Proceeding of Joint Automatic Control Conference, 1980. [3] E. F. Camacho and C. Bordons, Model Predictive Control, 2nd ed, Springer, 2005. [4] W. Wojsznis, J. Gudaz, T. Blevins and A. Mehta, "Practical approach to tuning MPC," ISA Transactions, vol. 42, pp. 149-162, 2003. [5] E. Ali and A. G. Ashraf, "On-line Tuning of Model Predictive Controllers Using Fuzzy Logic," The Canadian Journal of Chemical Engineering, vol. 81, pp. 1-11, Oct 2003. [6] A. Jiang and A. Jutan, "Response Surface Tuning Methods in Dynamic Matrix Control of a Pressure Tank System," Ind. Eng. Chem. Res., vol. 39, pp. 3835-3843, 2000. [7] A. R. Neshasteriz, A. Khaki Sedigh and H. Sadjadian, "Generalized predictive control and tuning of industrial processes with second order plus dead time models," Journal of Process Control, vol. 20, pp. 36-72, Jan 2010. [8] R. Shridhar and D. J. Cooper, "A Tuning Strategy for Unconstrained SISO Model Predictive Control," Ind. Eng. Chem. Res, vol. 36, pp. 729-746, 1997. [9] J. H. Lee, and Yu, Z.H, "Tuning of model predictive controllers for robust performance," Computer. Chem. Eng., vol. 18, pp. 15–37, 1994. [10] E. J. Iglesias, M. E, Sanjuán and C. A. Smith, "Tuning equation for dynamic matrix control in SISO loops," Ingeniería y Desarrollo, Issue 19, pp. 88-100, 2006. [11] A. R. Neshasteriz, A, Khaki-Sedigh and H, Sadjadian, "An Analysis of Variance Approach to Tuning of Generalized Predictive Controllers for Second Order plus Dead Time Models," 8th IEEE International Conference on Control & Automation, 2009. [12] L. Garriga and M. Soroush, "Model Predictive Control Tuning Methods: A Review," Ind. Eng. Chem. Res., vol. 49, pp. 3505–3515, 2010. [13] R. V. Hogg and J. Ledolter, Engineering statistics, MacMillan, 1987. [14] H. Scheffe, The Analysis of Variance, New York: Wiley, 1959. [15] R. A. Fisher, Statistical methods for research workers, Oliver and Boyd, Edinburgh, 1925. [16] R. A. Fisher, The design of experiments, Oliver and Boyd, Edinburgh, 1935. [17] A. M. Mora, J. J. Merelo, P. A. Castillo, J. L. J. Laredo and C. Cotta, "Influence of parameters on the performance of a MOACO algorithm for solving the bi-criteria military path-finding problem," Proceedings of the IEEE Congress on Evolutionary Computation, pp. 3507-3514, 2008. [18] V. A. Niskanen, "Prospects for integrating analysis of variance with soft computing," Information Sciences, vol. 134, pp. 135-166, 2001. [19] K. Barbe, W. Van Moer and Y. Rolain, "Using ANOVA in a Microwave Round-Robin Comparison," IEEE Transaction on Instrument, vol. 58, pp. 3490-3498, Oct 2009. [20] J. A. D. Rodrigues, E. C. V. Toledo and R. M. Filho, "A tuned approach of the predictive-adaptive GPC controller applied to a fed-batch bioreactor using complete factorial design," Computers and Chemical Engineering, vol. 26, pp. 1493-1500, 2002. [21] R. S. Bogartz, An introduction to the analysis of variance, Praeger, Connecticut, 1994. [22] M. Henson and D. Seborg, "Adaptive nonlinear control of a pH neutralization process," IEEE Trans. Control Syst. Technol., vol. 2, pp. 169–182, 1994. [23] J. Nie, A. P. Loh, and C. C. Hang, "Modeling pH neutralization process using fuzzy-neural approaches," Journal of fuzzy sets and systems, vol. 78, pp. 5-22, 1996. [24] D. Dougherty and D. Cooper, "A practical multiple model adaptive strategy for single-loop MPC," Control Engineering Practice, vol. 11, pp. 141–159, 2003. | ||
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