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Controlling Distributed Hyperbolic Plants with Adaptive Nonlinear Model Predictive Control

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Assessment and Future Directions of Nonlinear Model Predictive Control

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 358))

Abstract

A number of plants of technological interest include transport phenomena in which mass, or energy, or both, flow along one space dimension, with or without reactions taking place, but with neglected dispersion. This type of processes are described by hyperbolic partial differential equations [4] and is receiving an increasing attention in what concerns the application of Predictive Control [6]. Two examples considered are distributed collector solar fields [3, 10] and tubular bioreactors [5]. In both cases the manipulated variable is assumed to be the flow. For lack of space, only the first example is considered hereafter.

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References

  1. Adetola, V. and M. Guay, “Adaptive receding horizon control of nonlinear systems”, Proc. 6th IFAG Symp. on Nonlinear Control Systems—NOLCOS 2004, Stuttgart Germany, 1055–1060, (2004).

    Google Scholar 

  2. Barão M., Lemos J. M. and Silva, R. N., “Reduced complexity adaptative nonlinear control of a distributed collector solar field”, J. of Process Control, 12, 131–141, (2002).

    Article  Google Scholar 

  3. Camacho, E., M. Berenguel and F. Rubio, Advanced Control of Solar Plants, New York: Springer Verlag (1997).

    Google Scholar 

  4. Christofides, P. D., Nonlinear and Robust Control of PDE Systems, Birkhauser, (2001).

    Google Scholar 

  5. Dochain, D., J. P. Babary and Tali-Maamar, “Modeling and adaptive control of nonlinear distributed parameter bioreactors via orthogonal collocation ”, Automatica, 28, 873–883, (1992).

    Article  MATH  Google Scholar 

  6. Dubljevic, S., P. Mhaskar, N. H. El-Farra and P. D. Christofides, “ Predictive Control of Transport-Reactioon Processes”, Comp. and Chem. Eng., 29, 2335–2345, (2005).

    Article  Google Scholar 

  7. Mhaskar, P., N. H. El-Farra and Pd. D. Christofides (2005). “Predictive Control of Switched Nonlinear Systems With Scheduled Mode Transitions”, IEEE Trans. Autom. Control, 50, 1670–1680, (2005).

    Article  MathSciNet  Google Scholar 

  8. Primbs, J. A., V. Nevistic and J. Doyle, A Receding Generalization of Pointwise Min-Norm Controllers, http://citeseer.nj.nec.com, (1998).

  9. Shang, H., J. F. Forbes and M. Guay, “Model Predictive Control for Quasilinear Hyperbolic Distributed Parameter Systems”, Ind. Eng. Chem. Res., 43, 2140–2149, (2004).

    Article  Google Scholar 

  10. Silva, R. N., J. M. Lemos and L. M. Rato, “Variable sampling adaptive control of a distributed collector solar field”, IEEE Trans. Control Syst. Tech., 11, 765–772, (2003).

    Article  Google Scholar 

  11. Sontag, E., Mathematical Control Theory Springer-Verlag, 2nd Ed., (1998).

    Google Scholar 

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Igreja, J.M., Lemos, J.M., da Silva, R.N. (2007). Controlling Distributed Hyperbolic Plants with Adaptive Nonlinear Model Predictive Control. In: Findeisen, R., Allgöwer, F., Biegler, L.T. (eds) Assessment and Future Directions of Nonlinear Model Predictive Control. Lecture Notes in Control and Information Sciences, vol 358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72699-9_35

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  • DOI: https://doi.org/10.1007/978-3-540-72699-9_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72698-2

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