Accessibility navigation

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

Roberts, P. D. and Becerra, V. M. (1999) Model predictive control using dynamic integrated system optimisation and parameter estimation (DISOPE). In: IEE Two-Day Workshop on Model Predictive Control: Techniques and Applications, 28 Apr 1999, London, UK, 8/1-8/4,

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1049/ic:19990536


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.

Item Type:Conference or Workshop Item (Paper)
Divisions:Faculty of Science
ID Code:19229
Uncontrolled Keywords:continuous time systems, discrete time systems, iterative method, model predictive control, nonlinear control systems, optimal control, parameter estimation, system optimisation

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation