An iterative algorithm based on model-reality differences for discrete-time nonlinear stochastic optimal control problems
An iterative algorithm, which is called the integrated optimal control and parameter estimation algorithm, is developed for solving a discrete time nonlinear stochastic control problem. It is based on the integration of the principle of model-reality differences and Kalman filtering theory, where th...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/15129 |
| _version_ | 1848748810712383488 |
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| author | Kek, S. Aziz, M. Teo, Kok Lay Ahmad, R. |
| author_facet | Kek, S. Aziz, M. Teo, Kok Lay Ahmad, R. |
| author_sort | Kek, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | An iterative algorithm, which is called the integrated optimal control and parameter estimation algorithm, is developed for solving a discrete time nonlinear stochastic control problem. It is based on the integration of the principle of model-reality differences and Kalman filtering theory, where the dynamic integrated system optimization and parameter estimation algorithm are used interactively. In this approach, the weighted least-square output residual is included in the cost function by appropriately monitoring the weighted matrix. An improved linear quadratic Gaussian optimal control model, rather than the original optimal control problem, is solved. Subsequently, the model optimum is updated using the adjusted parameters induced by the differences between the real plant and the model used. These updated solutions converge to the true optimum, despite model-reality differences. For illustration, the optimal control of a nonlinear continuous stirred tank reactor problem is considered and solved by using the method proposed. |
| first_indexed | 2025-11-14T07:10:58Z |
| format | Journal Article |
| id | curtin-20.500.11937-15129 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:10:58Z |
| publishDate | 2013 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-151292017-09-13T15:04:45Z An iterative algorithm based on model-reality differences for discrete-time nonlinear stochastic optimal control problems Kek, S. Aziz, M. Teo, Kok Lay Ahmad, R. An iterative algorithm, which is called the integrated optimal control and parameter estimation algorithm, is developed for solving a discrete time nonlinear stochastic control problem. It is based on the integration of the principle of model-reality differences and Kalman filtering theory, where the dynamic integrated system optimization and parameter estimation algorithm are used interactively. In this approach, the weighted least-square output residual is included in the cost function by appropriately monitoring the weighted matrix. An improved linear quadratic Gaussian optimal control model, rather than the original optimal control problem, is solved. Subsequently, the model optimum is updated using the adjusted parameters induced by the differences between the real plant and the model used. These updated solutions converge to the true optimum, despite model-reality differences. For illustration, the optimal control of a nonlinear continuous stirred tank reactor problem is considered and solved by using the method proposed. 2013 Journal Article http://hdl.handle.net/20.500.11937/15129 10.3934/naco.2013.3.109 restricted |
| spellingShingle | Kek, S. Aziz, M. Teo, Kok Lay Ahmad, R. An iterative algorithm based on model-reality differences for discrete-time nonlinear stochastic optimal control problems |
| title | An iterative algorithm based on model-reality differences for discrete-time nonlinear stochastic optimal control problems |
| title_full | An iterative algorithm based on model-reality differences for discrete-time nonlinear stochastic optimal control problems |
| title_fullStr | An iterative algorithm based on model-reality differences for discrete-time nonlinear stochastic optimal control problems |
| title_full_unstemmed | An iterative algorithm based on model-reality differences for discrete-time nonlinear stochastic optimal control problems |
| title_short | An iterative algorithm based on model-reality differences for discrete-time nonlinear stochastic optimal control problems |
| title_sort | iterative algorithm based on model-reality differences for discrete-time nonlinear stochastic optimal control problems |
| url | http://hdl.handle.net/20.500.11937/15129 |