IJCCE  Vol.4 No.3 , August 2015
Multi-Objective Optimization for Active Disturbance Rejection Control for the ALSTOM Benchmark Problem
ABSTRACT
Based on a thing that it is difficult to choose the parameters of active disturbance rejection control for the non-linear ALSTOM gasifier, multi-objective optimization algorithm is applied in the choose of parameters. Simulation results show that performance tests in load change and coal quality change achieve better dynamic responses and larger scales of rejecting coal quality disturbances. The study provides an alternative to choose parameters for other control schemes of the ALSTOM gasifier.

Cite this paper
Huang, C. and Liu, Z. (2015) Multi-Objective Optimization for Active Disturbance Rejection Control for the ALSTOM Benchmark Problem. International Journal of Clean Coal and Energy, 4, 61-68. doi: 10.4236/ijcce.2015.43006.
References
[1]   Dixon, R., Pike, A.W. and Donne, M.S. (2000) The ALSTOM Benchmark Challenge on Gasifier Control. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 214, 389-394. http://dx.doi.org/10.1243/0959651001540744

[2]   Dixon, R. and Pike, A.W. (2004) Introduction to the 2nd ALSTOM Benchmark Challenge on Gasifier Control. In Control, ID255.

[3]   Dixon, R. (2005) Benchmark Challenge at Control 2004. Comput. Control Eng. IEE, 10, 21-23.

[4]   Asmar, B.N., Jones, W.E. and Wilson, J.A. (2000) A Process Engineering Approach to the ALSTOM Gasifier Problem. Proceedings of the Institution of Mechanical Engineers, 214, 441-452. http://dx.doi.org/10.1177/095965180021400601

[5]   Chin, C.S. and Munro, N. (2003) Control of the ALSTOM Gasifier Benchmark Problem Using H2 Methodology. Journal of Process Control, 13, 759-768. http://dx.doi.org/10.1016/S0959-1524(03)00008-8

[6]   Gatley, S.L., Bates, D.G. and Postlethwaite, I. (2004) H-Infinity Control and Anti-Windup Compensation of the Nonlinear ALSTOM Gasifier Model. In Control, ID 254.

[7]   Farag, A. and Werner, H. (2006) Structure Selection and Tuning of Multi-Variable PID Controllers for an Industrial Benchmark Problem. IEE Proceedings Control Theory and Applications, 153, 262-267. http://dx.doi.org/10.1049/ip-cta:20050061

[8]   Al Seyab, R.K., Cao, Y. and Yang, S.H. (2006) Predictive Control for the ALSTOM Gasifier Problem. IEE Proceedings Control Theory and Applications, 153, 293-301.

[9]   Taylor, C.J. and Shaban, E.M. (2006) Multivariable Proportional-Integral-Plus (PIP) Control of the ALSTOM Nonlinear Gasifier Simulation. IEE Proceedings Control Theory and Applications, 153, 277-285. http://dx.doi.org/10.1049/ip-cta:20050058

[10]   Wilson, J.A., Chew, M. and Jones, W.E. (2006) State Estimation-Based Control of a Coal Gasifier. IEE Proceedings Control Theory and Applications, 153, 270-276. http://dx.doi.org/10.1049/ip-cta:20050071

[11]   Simm, A. and Liu, G.P. (2006) Improving the Performance of the ALSTOM Baseline Controller Using Multiobjective Optimization. IEE Proceedings Control Theory and Applications, 153, 286-292. http://dx.doi.org/10.1049/ip-cta:20050131

[12]   Xue, Y.L., Li, D.H. and Gao, F.R. (2010) Multi-Objective Optimization and Selection for the PI Control of ALSTOM Gasifier Problem. Control Engineering Practice, 18, 67-76. http://dx.doi.org/10.1016/j.conengprac.2009.09.004

[13]   Tan, W., Lou, G. and Liang, L. (2011) Partially Decentralized Control for ALSTOM Gasifier. ISA Transactions, 50, 397-408. http://dx.doi.org/10.1016/j.isatra.2011.01.008

[14]   Huang, C.-E., Li, D.H. and Xue, Y.L. (2013) Active-Disturbance-Rejection-Control for the ALSTOM Gasifier Bench- mark Problem. Control Engineering Practice, 21, 556-564. http://dx.doi.org/10.1016/j.conengprac.2012.11.014

[15]   Deb, K., Pratap, A., Agarwal, S. and Meyarival, T. (2002) A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6, 182-196. http://dx.doi.org/10.1109/4235.996017

 
 
Top