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Multi-objective Optimization Control of Smith-Predictor Parameters in Superheated Steam Temperature System |
LIU Chang-Liang, MA Zeng-Hui |
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206 |
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Abstract The impact of Smith-predictor parameters on the control system performance is analyzed detailedly, and a multi-objective optimization control scheme of Smith-predictor parameters is proposed. The performance of the control system is improved by the model mismatch. Due to high order,large inertia and strong nonlinearity of the superheated steam temperature plant, a Smith-predictor parameter multi-objective self-tuning optimization control system is designed based on cascade PID. The control scheme is applied to a 600MW supercritical boiler superheated steam temperature control. The simulation results show that the proposed approach has a good robustness and can effectively overcome the long dead time and nonlinearity of the system, and it has much better performance compared with cascade PID and normal Smith predictor.
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Received: 13 January 2014
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[1] Liu X J, Liu J Z, Guan P. Neuro-Fuzzy Generalized Predictive Control of Boiler Steam Temperature. Journal of Control Theory and Applications, 2007, 5(1): 83-88 [2] Peng H, Ozaki T, Haggan-Ozaki V, et al. A Nonlinear Exponential ARX Model-Based Multivariable Generalized Predictive Control Strategy for Thermal Power Plants. IEEE Trans on Control Systems Technology, 2002, 10(2): 256-262 [3] Huang C Z, Bai Y, Liu X J. H-Infinity State Feedback Control for a Class of Networked Cascade Control Systems with Uncertain Delay. IEEE Trans on Industrial Informatics, 2010, 6( 1): 62-72
[4] Prasad G, lrwin G W, Swidenbank E, et al. Plant-Wide Predictive Control for a Thermal Power Plant Based on a Physical Plant Model. IEE Proceedings Control Theory and Applications, 2000, 147(5): 523-537 [5] Prasad G, Swidenbank E, Hogg B W. A Neural Net Model-Based Multivariable Long-Range Predictive Control Strategy Applied in Thermal Power Plant Control. IEEE Trans on Energy Conversion, 1998, 13(2): 176-182 [6] Glickman S, Kulessky R, Nudelman G. Identification-Based PID Control Tuning for Power Station Processes. IEEE Trans on Control Systems Technology, 2004, 12(1): 123-132 [7] Moelbak T. Advanced Control of Superheater Steam Temperatures-An Evaluation Based on Practical Applications. Control Engineering Practice, 1999, 7(1): 1-10 [8] Ioannides A C, Rogers G J, Latham V. Stability Limits of a Smith Controller in Simple Systems Containing a Time Delay. International Journal of Control, 1979, 29(4): 557-563 [9] Horowitz I. Some Properties of Delayed Controls (Smith Regulator). International Journal of Control, 1983, 38(5): 977-990 [10] Marshall J E, Salehi S V. Improvement of System Performance by the Use of Time-delay Elements. IEEE Proceedings D Control Theory and Applications, 1982, 129(5): 177-181 [11] Walton K, Marshall J E. Mismatch in a Predictor Control Scheme: Some Closed-Form Solutions. International Journal of Control, 1984, 40(2): 403-419 [12] Huang J J, DeBra D B. Automatic Smith-Predictor Tuning Using Optimal Parameter Mismatch. IEEE Trans on Control Systems Technology, 2002, 10(3): 447-459 [13] Fan Y S,Xu Z G, Chen L J. Study of Adaptive Fuzzy Control of Boiler Superheated Steam Temperature Based on Dynamic Mechanism Analysis. Proceedings of the CSEE, 1997, 17(1): 23-28 (in Chinese) (范永胜,徐治皋,陈来九.基于动态特性机理分析的锅炉热汽温自适应模糊控制系统研究.中国电机工程学报, 1997, 17(1): 23-28) [14] Kaya I. IMC Based Automatic Tuning Method for PID Controllers in a Smith Predictor Configuration. Computers and Chemical Engineering, 2004, 28(3): 281-290 [15] Hang C C, Astrom K J, Ho W K. Refinements of the Ziegler-Nichols Tuning Formula. IEE Proceedings D Control Theory and Applications, 1991, 138(2): 111-118 [16] str m K J, Hgglund T, Hang C C, et al. Automatic Tuning and Adaptation for PID Controllers-A Survey. Control Engineering Practice, 1993, 1(4): 699-714 [17] Deb K, Pratap A, Agarwal S, et al. A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Trans on Evolutionary Computation, 2002, 6(2): 182-197 |
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