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Neural Network Model Predictive Control of a Wastewater Treatment Bioprocess

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Intelligent Decision Technologies

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 10))

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Abstract

This paper deals with the design of a nonlinear model predictive control (NMPC) scheme for the regulation of the acetate concentration in a biomethanation process – wastewater biodegradation with production of methane gas that takes place inside a Continuous Stirred Tank Bioreactor. The NMPC control structure is based on a radial basis function neural network used as on-line approximator to learn the nonlinear characteristics of process. Minimization of the cost function is realised using the Levenberg–Marquardt numerical optimisation method. Some simulation results are given to illustrate the efficiency of the proposed control strategy.

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References

  1. Bastin, G., Dochain, D.: On-line Estimation and Adaptive Control of Bioreactors. Elsevier, Amsterdam (1990)

    Google Scholar 

  2. Bastin, G.: Nonlinear and adaptive control in biotechnology: a tutorial. In: Proc. ECC 1991 Conf., Grenoble, pp. 2001–2012 (1991)

    Google Scholar 

  3. Selişteanu, D., Petre, E.: Vibrational control of a class of bioprocesses. Contr. Eng. and App. Inf. 3(1), 39–50 (2001)

    Google Scholar 

  4. Camacho, E.F., Bordons, C.: Model Predictive Control, 2nd edn. Springer, Heidelberg (2004)

    MATH  Google Scholar 

  5. Hayakawa, T., Haddad, W.M., Hovakimyan, N.: Neural network adaptive control for a class of nonlinear uncertain dynamical systems with asymptotic stability guarantees. IEEE Trans. on Neural Networks 19, 80–89 (2008)

    Article  Google Scholar 

  6. Petre, E., Selişteanu, D., Şendrescu, D.: Neural Networks Based Adaptive Control for a Class of Time Varying Nonlinear Processes. In: Int. Conf. on Control, Automation and Systems ICCAS 2008, COEX, Seoul, Korea, October 14-17, pp. 1355–1360 (2008)

    Google Scholar 

  7. Funahashi, K.: On the approximate realization of continuous mappings by neural networks. Neural Networks 2, 183–192 (1989)

    Article  Google Scholar 

  8. Yu, W., Li, X.: Some new results on system identification with dynamic neural networks. IEEE Trans. Neural Networks 12(2), 412–417 (2001)

    Article  Google Scholar 

  9. Isidori, A.: Nonlinear Control Systems, 3rd edn. Springer, Berlin (1995)

    MATH  Google Scholar 

  10. Petre, E.: Nonlinear Control Systems – Applications in Biotechnology, 2nd edn. Universitaria, Craiova (2008) (in Romanian)

    Google Scholar 

  11. Dochain, D., Vanrolleghem, P.: Dynamical Modelling and Estimation in Wastewater Treatment Processes. IWA Publishing (2001)

    Google Scholar 

  12. Mayne, D.Q., Rawlings, J.B., Rao, C.V., Scokaert, P.O.: Constrained model predictive control: stability and optimality. Automatica 36, 789–814 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  13. Spooner, J.T., Passino, K.M.: Decentralized adaptive control of nonlinear systems using radial basis neural networks. IEEE Trans. on Autom. Control 44(11), 2050–2057 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  14. Eaton, J.W., Rawlings, J.R.: Feedback control of nonlinear processes using online optimization techniques. Computers and Chemical Engineering 14, 469–479 (1990)

    Article  Google Scholar 

  15. Wang, Y., Boyd, S.: Fast model predictive control using online optimization. In: Proc. of the 17th World Congress of International Federation of Automatic Control, WC-IFAC 2008 (2008)

    Google Scholar 

  16. Kouvaritakis, B., Cannon, M.: Nonlinear Predictive Control: Theory and Practice. IEE (2001)

    Google Scholar 

  17. Nocedal, J., Wright, S.J.: Numerical Optimization. Springer, Heidelberg (1999)

    Book  MATH  Google Scholar 

  18. Petre, E., Selişteanu, D., Şendrescu, D.: Adaptive control strategies for a class of anaerobic depollution bioprocesses. In: Proc. of Int. Conf. on Automation, Quality and Testing, Robotics, Cluj-Napoca, Romania, Tome II, May 22-25, pp. 159–164 (2008)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Automatic Control, University of Craiova, A.I. Cuza 13, Craiova, Romania

    Dorin Şendrescu, Emil Petre, Dan Popescu & Monica Roman

Authors
  1. Dorin Şendrescu
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  2. Emil Petre
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  3. Dan Popescu
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  4. Monica Roman
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Editor information

Editors and Affiliations

  1. Graduate School of Information, Production and Systems (IPS), Waseda University, 2-7 Hibikino Wakamatsuku, 808-0135, Fukuoka, Kitakyushu, Japan

    Junzo Watada

  2. Sellinger School of Business and Management, Loyola University Maryland, 4501 N Charles Street, 21210, Baltimore, MD, USA

    Gloria Phillips-Wren

  3. School of Electrical and Information Engineering, University of South Australia, Mawson Lakes Campus Adelaide, 5095, South Australia, SA, Australia

    Lakhmi C. Jain

  4. KES International, Shoreham-by-seaWest Sussex, PO Box 2115, BN43 9AF, United Kingdom

    Robert J. Howlett

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© 2011 Springer-Verlag Berlin Heidelberg

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Şendrescu, D., Petre, E., Popescu, D., Roman, M. (2011). Neural Network Model Predictive Control of a Wastewater Treatment Bioprocess. In: Watada, J., Phillips-Wren, G., Jain, L.C., Howlett, R.J. (eds) Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 10. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22194-1_20

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  • DOI: https://doi.org/10.1007/978-3-642-22194-1_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22193-4

  • Online ISBN: 978-3-642-22194-1

  • eBook Packages: EngineeringEngineering (R0)

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