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Stochastic HYPE is a novel process algebra that models stochastic, instantaneous and continuous behaviour. It develops the flow-based approach of the hybrid process algebra HYPE by replacing non-urgent events with events with exponentially-distributed durations and also introduces random resets. The random resets allow for general stochasticity, and in particular allow for the use of event durations drawn from distributions other than the exponential distribution. To account for stochasticity, the semantics of stochastic HYPE target piecewise deterministic Markov processes (PDMPs), via intermediate transition-driven stochastic hybrid automata (TDSHA) in contrast to the hybrid automata used as semantic target for HYPE. Stochastic HYPE models have a specific structure where the controller of a system is separate from the continuous aspect of this system providing separation of concerns and supporting reasoning. A novel equivalence is defined which captures when two models have the same stochastic behaviour (as in stochastic bisimulation), instantaneous behaviour (as in classical bisimulation) and continuous behaviour. These techniques are illustrated via an assembly line example.
We present a new method for the automated synthesis of safe and robust Proportional-Integral-Derivative (PID) controllers for stochastic hybrid systems. Despite their widespread use in industry, no automated method currently exists for deriving a PID
We demonstrate the modelling of opportunistic networks using the process algebra stochastic HYPE. Network traffic is modelled as continuous flows, contact between nodes in the network is modelled stochastically, and instantaneous decisions are modell
The process algebra HYPE was recently proposed as a fine-grained modelling approach for capturing the behaviour of hybrid systems. In the original proposal, each flow or influence affecting a variable is modelled separately and the overall behaviour
This work targets the development of an efficient abstraction method for formal analysis and control synthesis of discrete-time stochastic hybrid systems (SHS) with linear dynamics. The focus is on temporal logic specifications, both over finite and
We consider the problem of designing control laws for stochastic jump linear systems where the disturbances are drawn randomly from a finite sample space according to an unknown distribution, which is estimated from a finite sample of i.i.d. observat