The paper focuses on active fault diagnosis (AFD) of large scale systems. The multiple model framework is considered and two architectures are treated: the decentralized and the distributed one. An essential part of the AFD algorithm is state estimation, which must be supplemented with a mechanism to achieve feasible implementation in the multiple model framework. In the paper, the generalized pseudo Bayes and interacting multiple model estimation algorithms are considered. They are reformulated for a given model of a large scale system. Performance of both AFD architectures is analyzed for different combinations of multiple model estimation algorithms using a numerical example.
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In the paper a synthesis of suboptimal control laws a large scale stochastic system composed of interacting linear subsystems is presented. A two-level hierarchical control structure with a coordinator and local controllers having access to different information is assumed. The possibility of partially decomposed calculations is shown as well as realization of decentralized local control. An illustrative example is presented.
Coalgebra and coinduction provide new results and insights for modular supervisory control of discrete-event systems (DES), where the overall system is composed of subsystems that are combined in synchronous (parallel) product. Modular supervisory control is studied within the coalgebraic framework. Coinduction has been used to define an operation on languages called supervised product, and synchronous product is defined by coinduction. We have shown recently that the supremal controllable sublanguage of a given language can be defined by coinduction as well. We study the commutativity between the synchronous product and supremal controllable and normal sublanguage. The results guarantee that under the conditions derived in the paper control synthesis can be done locally without affecting the optimality of the solution.
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In the paper a synthesis of a control law for a large scale stochastic system is presented. The system composed of coupled linear subsystems and quadratic performance index which should be minimized, is considered. The problem is solved in a two-level hierarchical control structure wtih a coordinator on an upper level and local controllers on a lower level. An algorithm, in which it is possible to partially decompose calculations and to realize decentralized control, is proposed. a simple example is presented.
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