Model predictive control using dynamic integrated system optimisation and parameter estimation (DISOPE)

P. D. Roberts, Victor Manuel Becerra

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    DISOPE is a technique for solving optimal control problems where there are differences in structure and parameter values between reality and the model employed in the computations. The model reality differences can also allow for deliberate simplification of model characteristics and performance indices in order to facilitate the solution of the optimal control problem. The technique was developed originally in continuous time and later extended to discrete time. The main property of the procedure is that by iterating on appropriately modified model based problems the correct optimal solution is achieved in spite of the model-reality differences. Algorithms have been developed in both continuous and discrete time for a general nonlinear optimal control problem with terminal weighting, bounded controls and terminal constraints. The aim of this paper is to show how the DISOPE technique can aid receding horizon optimal control computation in nonlinear model predictive control.
    Original languageEnglish
    Title of host publicationIEE two-day workshop on model predictive control
    Subtitle of host publicationtechniques and applications day 1 (ref. no. 1999/095)
    PublisherIET Conference Publications
    Publication statusPublished - 1999


    • continuous time systems, discrete time systems, iterative method, model predictive control, nonlinear control systems, optimal control, parameter estimation, system optimisation


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