This thesis presents a formal method for the the design of optimal and provably correctudprocedural controllers for chemical processes modelled as Stochastic Discrete Event Systemsud(SDESs). The thesis extends previous work on Procedural Control Theory (PCT) [1],udwhich used formal techniques for the design of automation Discrete Event Systems (DESs).udMany dynamic processes for example, batch operations and the start-up and shut down ofudcontinuous plants, can be modelled as DESs. Controllers for these systems are typicallyudof the sequential type.udMost prior work on characterizing the behaviour of DESs has been restricted to deterministicudsystems. However, DESs consisting of concurrent interacting processes presentuda broad spectrum of uncertainty such as uncertainty in the occurrence of events. Theudformalism of weighted probabilistic Finite State Machine (wp-FSM) is introduced forudmodelling SDESs and pre-de ned failure models are embedded in wp-FSM to describeudand control the abnormal behaviour of systems. The thesis presents e cient algorithmsudand procedures for synthesising optimal procedural controllers for such SDESs.udThe synthesised optimal controllers for such stochastic systems will take into considerationudprobabilities of events occurrence, operation costs and failure costs of events inudmaking optimal choices in the design of control sequences. The controllers will force theudsystem from an initial state to one or more goal states with an optimal expected cost andudwhen feasible drive the system from any state reached after a failure to goal states.udOn the practical side, recognising the importance of the needs of the target enduduser, the design of a suitable software implementation is completed. The potential of bothudthe approach and the supporting software are demonstrated by two industry case studies.udFurthermore, the simulation environment gPROMS was used to test whether the operatingudspeci cations thus designed were met in a combined discrete/continuous environment.
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