Symbolic Computation of Nonblocking Control Function for Timed Discrete Event Systems

In this paper, we symbolically compute a minimally restrictive nonblocking supervisor for timed discrete event systems, in the supervisory control theory context. The method is based on Timed Extended Finite Automata, which is an augmentation of extended finite automata (EFAs) by incorporating discrete time into the model. EFAs are ordinary automaton extended with discrete variables, guard expressions and action functions. To tackle large problems all computations are based on binary decision diagrams (BDDs). The main feature of this approach is that the BDD-based fixed-point computations is not based on “tick” models that have been commonly used in this area, leading to better performance in many cases. As a case study, we effectively computed the minimally restrictive nonblocking supervisor for a well-known production cell

Symbolic Supervisory Control of Timed Discrete Event Systems

With the increasing complexity of computer systems, it is crucial to have efficient design of correct and well-functioning hardware and software systems. To this end, it is often desired to control the behavior of systems to possess some desired properties. A specific class of systems is called discrete event systems (DES). DES deal with `discrete' quantities, e.g., ``number of robots in a manufacturing cell'', and their processes are driven by instantaneous `events', e.g., ``start of a machine''. In this thesis, the focus is on DES and an extension of such systems, which also considers the time points at which the events may occur, called \emph{timed DES (TDES)}. Real-time applications such as communication networks, manufacturing facilities, or the execution of a computer program, can be considered into TDES. Having a DES or TDES, with some given specifications, by utilizing a well-known mathematical framework, called supervisory control theory (SCT), it is possible to automatically generate a supervisor that restricts the system's behavior towards the specifications, only when it is necessary. Applying the SCT to large and complex systems, typically follows with some issues, concerning computational complexity and modeling aspects, which is tackled in this thesis. We model DES by extended finite automata (EFAs), state transition models that contain discrete-valued variables. TDES are modeled by an augmentation of EFAs, called timed EFAs (TEFAs), which contain a set of discrete-valued clocks. Based on EFAs or TEFAs, the supervisor can be symbolically computed, using binary decision diagrams (BDDs), data structures that could, in many cases, lead to smaller representation of the state space. For complex systems, the computed supervisor may consist of many states, causing representation and implementation difficulties. To tackle this, based on the states of the supervisor, we symbolically compute logical constraints that will be attached to the original models to restrict the system's behavior. Consequently, we present a framework, where given a set of EFAs or TEFAs, the supervisor is computed using BDDs, and represented in a modular manner based on the computed logical constraints. The framework has been developed, implemented, and applied to industrial case studies

Process Mining of Programmable Logic Controllers: Input/Output Event Logs

This paper presents an approach to model an unknown Ladder Logic based Programmable Logic Controller (PLC) program consisting of Boolean logic and counters using Process Mining techniques. First, we tap the inputs and outputs of a PLC to create a data flow log. Second, we propose a method to translate the obtained data flow log to an event log suitable for Process Mining. In a third step, we propose a hybrid Petri net (PN) and neural network approach to approximate the logic of the actual underlying PLC program. We demonstrate the applicability of our proposed approach on a case study with three simulated scenarios

Practical applications of probabilistic model checking to communication protocols

Probabilistic model checking is a formal verification technique for the analysis of systems that exhibit stochastic behaviour. It has been successfully employed in an extremely wide array of application domains including, for example, communication and multimedia protocols, security and power management. In this chapter we focus on the applicability of these techniques to the analysis of communication protocols. An analysis of the performance of such systems must successfully incorporate several crucial aspects, including concurrency between multiple components, real-time constraints and randomisation. Probabilistic model checking, in particular using probabilistic timed automata, is well suited to such an analysis. We provide an overview of this area, with emphasis on an industrially relevant case study: the IEEE 802.3 (CSMA/CD) protocol. We also discuss two contrasting approaches to the implementation of probabilistic model checking, namely those based on numerical computation and those based on discrete-event simulation. Using results from the two tools PRISM and APMC, we summarise the advantages, disadvantages and trade-offs associated with these techniques

Process algebra for performance evaluation

This paper surveys the theoretical developments in the field of stochastic process algebras, process algebras where action occurrences may be subject to a delay that is determined by a random variable. A huge class of resource-sharing systems – like large-scale computers, client–server architectures, networks – can accurately be described using such stochastic specification formalisms. The main emphasis of this paper is the treatment of operational semantics, notions of equivalence, and (sound and complete) axiomatisations of these equivalences for different types of Markovian process algebras, where delays are governed by exponential distributions. Starting from a simple actionless algebra for describing time-homogeneous continuous-time Markov chains, we consider the integration of actions and random delays both as a single entity (like in known Markovian process algebras like TIPP, PEPA and EMPA) and as separate entities (like in the timed process algebras timed CSP and TCCS). In total we consider four related calculi and investigate their relationship to existing Markovian process algebras. We also briefly indicate how one can profit from the separation of time and actions when incorporating more general, non-Markovian distributions

Model based fault diagnosis for hybrid systems : application on chemical processes

The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless, this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering

Causality and Temporal Dependencies in the Design of Fault Management Systems

Reasoning about causes and effects naturally arises in the engineering of safety-critical systems. A classical example is Fault Tree Analysis, a deductive technique used for system safety assessment, whereby an undesired state is reduced to the set of its immediate causes. The design of fault management systems also requires reasoning on causality relationships. In particular, a fail-operational system needs to ensure timely detection and identification of faults, i.e. recognize the occurrence of run-time faults through their observable effects on the system. Even more complex scenarios arise when multiple faults are involved and may interact in subtle ways. In this work, we propose a formal approach to fault management for complex systems. We first introduce the notions of fault tree and minimal cut sets. We then present a formal framework for the specification and analysis of diagnosability, and for the design of fault detection and identification (FDI) components. Finally, we review recent advances in fault propagation analysis, based on the Timed Failure Propagation Graphs (TFPG) formalism.Comment: In Proceedings CREST 2017, arXiv:1710.0277