Abstract
The B-spline neural networks are used to model probability density function (PDF) with least square algorithm, the controllers are designed accordingly. Both the modeling and control methods are tested with molecular weight distribution (MWD) through simulation.
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References
Wang, H.: Bounded Dynamic Stochastic Distributions Modeling and Control. Springer, London (2000)
Yue, H., Wang, H.: Recent Developments in Stochastic Distribution Control: A Review. Journal of Measurement and Control 36, 209–215 (2003)
Guo, L., Wang, H.: Pseudo-PID Tracking Control for a Class of Output PDFs of General Non-Gaussian Stochastic Systems. In: Proceedings of the 2003 American Control Conference, Denver, Colorado, USA, pp. 362–367 (2003)
Wang, H.: Control of the Output Probability Density Functions For a Class of Nonlinear Stochastic Systems. In: Proceedings of the IFAC Workshop on Algorithms and Architectures for Real-time Control, Cancun, Mexico, pp. 95–99 (1998)
Wang, H., Zhang, J.H.: Control of the Output Stochastic Distributions Via Lyapunov Function Analysis. In: Proceedings of IEEE International Conference on Control Applications CACSD, Glasgow, pp. 927–931 (2002)
Clarke-Pringle, T.L., MacGregor, J.F.: Optimization of Molecular-Weight Distribution using Batch-to-Batch Adjustments. Industrial and Engineering Chemistry Research 37, 3660–3669 (1998)
Crowley, T.J., Choi, K.Y.: Calculation of Molecular Weight Distribution from Molecular Weight Moments in Free Radical Polymerization. Industrial and Engineering Chemistry Research 36, 1419–1423 (1997)
Soares, J.B., Kim, J.D., Rempel, G.L.: Analysis and Control of the Molecular Weight and Chemical Composition Distributions of Polyolefins Made with Metallocene and Ziegler-Natta Catalysts. Industrial and Engineering Chemistry Research 36, 1144–1150 (1997)
Vicente, M., BenAmor, S., Gugliotta, L.M., Leiza, J.R., Asua, J.M.: Control of Molecular Weight Ddistribution in Emulsion Polymerization using On-Line Reaction Calorimetry. Industrial and Engineering Chemistry Research 40, 218–227 (2001)
Vicente, M., Sayer, C., Leiza, J.R., Arzamendi, G., Lima, E.L., Pinto, J.C., Asua, J.M.: Dynamic Optimization of Non-Linear Emulsion Co-Polymerization Systems Open-Loop Control of Composition and Molecular Weight Distribution. J. Chemical Engineering 85, 339–349 (2002)
Chen, Z.X., Li, S.G.: Data Approximation and the Numerical Solution to the Common Differential Equations. Xi’an Jiaotong University Publishing Company, Xi’an (2000)
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Zhang, J., Yue, H. (2007). Steady-State Modeling and Control of Molecular Weight Distributions in a Styrene Polymerization Process Based on B-Spline Neural Networks. In: Liu, D., Fei, S., Hou, ZG., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72383-7_39
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DOI: https://doi.org/10.1007/978-3-540-72383-7_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72382-0
Online ISBN: 978-3-540-72383-7
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