Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/11959
Title: | A Compositional Approach for Verifying Sampled-Data Supervisory Control |
Authors: | Baloch, Mahvash |
Advisor: | Leduc, Ryan Malik, Robi |
Department: | Computing and Software |
Keywords: | Discrete Event Systems;Supervisory Control;Sampled Data Supervisory Control;Compositional Verification;Controls and Control Theory;Controls and Control Theory |
Publication Date: | Apr-2012 |
Abstract: | <p>Sampled-data supervisory control deals with timed discrete event systems (TDES) where the supervisors are to be implemented as sampled-data controllers. A sampled-data controller views the system as a series of inputs and outputs and is controlled by a periodic clock. It samples its inputs, changes state, and updates its outputs on each clock edge (the tick event). The sampled-data supervisory control framework provides a set of conditions that the TDES system must satisfy to ensure its correct behaviour in order to be implemented as sampled data controllers. A serious limitation for automatic verification of systems is the size of the system's synchronous product. To overcome this limitation, we propose the use of a compositional approach to the verification of sampled-data supervisory control. In this approach, first we recast the required conditions for sampled-data supervisory control in terms of other properties such as language inclusion, nonblocking or controllability, which already have existing compositional methods and algorithms. This makes the sampled-data properties suitable for compositional verification, considerably increasing the size of systems that can be handled using sampled-data supervisory control. We also develop and implement a set of algorithms for the compositional verification of these sampled-data properties. We provide an example of the SD Controlled Flexible Manufacturing System to test our algorithms.</p> |
URI: | http://hdl.handle.net/11375/11959 |
Identifier: | opendissertations/6886 7924 2710877 |
Appears in Collections: | Open Access Dissertations and Theses |
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