Nuclear power plant optimal control by successive linear programming

  • S. Thangasamy
  • R. N. Ray
  • M. C. Srisailam
Contributed Papers


An attempt to find optimal controls for an extremely load-following nuclear power plant during large load pick-ups is reported in this paper. The choice of the numerical method to solve this highly constrained dynamic optimization problem is discussed. The results reported demonstrate the efficacy of the successive linear programming method in tackling this problem without recourse to model linearization.

Key Words

Load following dynamic optimization mathematical programming successive linear programming 


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  1. 1.
    Basile, F., et al.,PWR Development for Nuclear Ship Propulsion: Reactor Control and in Core Instrumentation Design, Proceedings of the Symposium on Nuclear Ships, Hamburg, Germany, 1971.Google Scholar
  2. 2.
    Thangasamy, S.,Optimal Control of a Nuclear Power Plant by Successive Linear Programming, PhD Thesis, Department of Electrical Engineering, Indian Institute of Technology, Bombay, India, 1982.Google Scholar
  3. 3.
    Grumbach, R., andBlomsnes, B.,Development and Application of Advanced Concepts for Nuclear Plant and Core Control, Proceedings of the Symposium on Nuclear Power Plant Control and Instrumentation, IAEA, 1973.Google Scholar
  4. 4.
    Thangasamy, S., andRay, R. N.,Reduced-Order Models for Real-Time Simulation of a Nuclear Power Plant, Proceedings of the Fifth National Systems Conference, PAU, Ludhiana, India, 1978.Google Scholar
  5. 5.
    Price, H. J., andMohler, R. R.,Computation of Optimal Controls for a Nuclear Rocket Reactor, IEEE Transactions on Nuclear Science, Vol. NS-15, pp. 65–73, 1968.Google Scholar
  6. 6.
    Kirk, D. E.,Optimal Control Theory, Prentice Hall, Englewood Cliffs, New Jersey, 1970.Google Scholar
  7. 7.
    Lasdon, L. S.,An Interior Penalty Method for Inequality Constrained Optimal Control Problems, IEEE Transactions on Automatic Control, Vol. AC-12, pp. 388–395, 1967.Google Scholar
  8. 8.
    Bellman, R. E., andDreyfus, S. E.,Applied Dynamic Programming, Princeton University Press, Princeton, New Jersey, 1962.Google Scholar
  9. 9.
    Tabak, D., andKuo, B. C.,Optimal Control by Mathematical Programming, Prentice Hall, New York, New York, 1971.Google Scholar
  10. 10.
    Haugset, K., andLeikkonen, I.,Nuclear Reaction Control by Multistage Mathematical Programming, Modelling, Identification, and Control, Vol. 1, pp. 119–133, 1980.Google Scholar
  11. 11.
    Cullum, J.,Finite-Dimensional Approximations of State-Constrained Continuous Optimal Control Problems, SIAM Journal on Control, Vol. 10, pp. 649–670, 1972.Google Scholar
  12. 12.
    Lasdon, L. S., et al.Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming, ACM Transactions on Mathematical Software, Vol. 4, pp. 34–50, 1978.Google Scholar
  13. 13.
    Dantzig, G. B.,Linear Control Processes and Mathematical Programming, SIAM Journal on Control, Vol. 4, pp. 56–60, 1966.Google Scholar
  14. 14.
    Griffith, R. E., andStewart, R. A.,A Nonlinear Programming Technique for the Optimization of Continuous Processing Systems, Management Science, Vol. 7, pp. 379–392, 1961.Google Scholar
  15. 15.
    Batchelor, A. S. J., andBeale, E. M. L.,A Revised Method of Conjugate Gradient Approximation Programming, Survey of Mathematical Programming, Vol. 1, Edited by A. Prekopa, North-Holland, Amsterdam, Holland, 1979.Google Scholar
  16. 16.
    Baier, H.,Mathematical Programming in Engineering Design Problems, Numerical Optimization of Dynamic Systems, Edited by L. C. W. Dixon and G. P. Szego, North-Holland, Amsterdam, Holland, 1980.Google Scholar
  17. 17.
    Buzby, B. R.,Techniques and Experience: Solving Really Big Nonlinear Programs, Optimization Methods for Resource Allocation, Edited by R. Cottle and J. Krarup, English Universities Press, London, England, 1974.Google Scholar
  18. 18.
    Lasdon, L. S., andWaren, A. D.,Survey of Nonlinear Programming Applications, Operations Research, Vol. 28, pp. 1029–1073, 1980.Google Scholar
  19. 19.
    Rosen, J. B.,Iterative Solution of Nonlinear Optimal Control Problems, SIAM Journal on Control, Vol. 4, pp. 223–244, 1966.Google Scholar
  20. 20.
    Halkin, H.,A Maximum Principle of the Pontryagin Type for Systems Described by Nonlinear Difference Equations, SIAM Journal on Control, Vol. 4, pp. 90–111, 1966.Google Scholar
  21. 21.
    Ball, S. J., andAdams, R. K.,matexp:A General-Purpose Digital Computer Program for Solving Ordinary Differential Equations by Matrix Exponential Method, Oak Ridge National Laboratory, Report No. ORNL-TM-1933, 1967.Google Scholar
  22. 22.
    Moler, C., andLoan, C. V.,Nineteen Dubious Ways to Compute the Exponential of a Matrix, SIAM Review, Vol. 20, pp. 801–836, 1978.Google Scholar
  23. 23.
    opalineProgrammation Lineare, Manuel d'Utilisation, CII, Louvenciennes, France, 1972.Google Scholar

Copyright information

© Plenum Publishing Corporation 1984

Authors and Affiliations

  • S. Thangasamy
    • 1
  • R. N. Ray
    • 1
  • M. C. Srisailam
    • 2
  1. 1.Reactor Control DivisionBhabha Atomic Research CentreBombayIndia
  2. 2.Department of Electrical EngineeringIndian Institute of TechnologyBombayIndia

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