In this dissertation, the class of problems where a performance index must be optimized at the final time of operation of a batch process, is studied for various process conditions. First, optimal state feedback laws for end-point optimization of dynamic systems are derived where the state model is a nonlinear function of the manipulated input and the system states. The necessary conditions for optimality are cast in terms of the system Lie brackets and the adjoint states. An optimal state feedback law is derived which is independent of adjoint states. The nature of the optimal state feedback law (static or dynamic) is characterized in terms of the system dynamics. In the next phase of this work, this optimal feedback approach is extended to include the effect of measurable disturbances. It is found that depending on the degree of singularity with respect to manipulated input and/or disturbance input, the feedforward/feedback laws are either static or dynamic. In the final phase of this research, optimal state feedback laws are derived for on-line optimization of batch processes with two manipulated inputs where one input appears nonlinearly and the other appears linearly in the state model. As illustrative examples of application of the proposed state feedback laws, several end-point optimization problems in batch chemical reactors are considered. / Source: Dissertation Abstracts International, Volume: 57-03, Section: B, page: 1964. / Major Professor: Srinivas Palanki. / Thesis (Ph.D.)--The Florida State University, 1996.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_77685 |
| Contributors | Rahman, A. K. M. Shamsur., Florida State University |
| Source Sets | Florida State University |
| Language | English |
| Detected Language | English |
| Type | Text |
| Format | 215 p. |
| Rights | On campus use only. |
| Relation | Dissertation Abstracts International |
Page generated in 0.1486 seconds