Discrete event dynamic systems最新文献

P-time event graphs are discrete event systems suitable for modeling processes in which tasks must be executed in predefined time windows. Their dynamics can be represented by max-plus linear-dual inequalities (LDIs), i.e., systems of linear dynamical inequalities in the primal and dual operations of the max-plus algebra. We define a new class of models called switched LDIs (SLDIs), which allow to switch between different modes of operation, each corresponding to a set of LDIs, according to a sequence of modes called schedule. In this paper, we focus on the analysis of SLDIs when the considered schedule is fixed and either periodic or intermittently periodic. We show that SLDIs can model a wide range of applications including single-robot multi-product processing networks, in which every product has different processing requirements and corresponds to a specific mode of operation. Based on the analysis of SLDIs, we propose algorithms to compute: i. minimum and maximum cycle times for these processes, improving the time complexity of other existing approaches; ii. a complete trajectory of the robot including start-up and shut-down transients.

In this paper, we deal with the problem of coordinating multiple agents to accomplish a global task. This problem consists of a set of agents divided into teams of homogeneous agents that interact with each other in order to autonomously complete a common global task. Due to the fact that agents in a team are exactly the same both in hardware and control software, the open-loop behavior of any agent in a team can be represented by a template, as well as its local control specifications. Our approach is based on the Supervisory Control Theory and it derives sufficient conditions that allow us to synthesize for each team a local supervisor template from templates associated with the team and the global task model in such a way that, when this supervisor template is instantiated for the other agents in the team, the global task can be completed by the coordinated action of all agents in the system. Our sufficient conditions also guarantee that a computed set of supervisor templates does not need to be recomputed or reconfigured whenever agents are added or removed from teams. An example of 3D robotic construction is provided to illustrate our approach.

This paper addresses the verification of non-blockingness for modular discrete-event systems, i.e., discrete-event systems that are composed from component models. For such systems, the explicit construction of a monolithic representation turns out intractable for relevant applications, since such a construction in general is of exponential cost w.r.t. the number of components. One well established approach to circumvent the need for a monolithic representation for the verification task at hand is to alternate (a) the substitution of individual components by abstractions and (b) the composition of only a small number of strategically chosen components at a time. When successful, one ends up with a single moderately sized automaton which does not represent the overall behaviour in any detail but which does block if and only if the original modular system fails to be non-conflicting. This approach is referred to as compositional verification and originates from the field of process algebra with more recent adaptations to finite automata models. The main contribution of the present study is the development of a number of abstraction rules valid for compositional verification of non-conflictingness in the presence of global event priorities, i.e., where high priority events from one component possibly preempt events with lower priority of all components.

Simulation models have been described using different perspectives, or worldviews. In the process interaction world view (PI), every entity is modeled by a sequence of actions describing its life cycle, offering a comprehensive model that groups the events involving each entity. In this paper we describe (pi ) HyFlow, a formalism for representing hybrid models using a set of communicating processes. This set is dynamic, enabling processes to be created and destroyed at runtime. Processes are encapsulated into (pi ) HyFlow base models and communicate through shared memory. (pi ) HyFlow, however, can guarantee modularity by enforcing that models can only communicate by input and output interfaces. (pi ) HyFlow extends current PI approaches by providing support for HyFlow concepts of sampling and dense (continuous) outputs, in addition to the more traditional event-based communication. Likewise HyFlow, (pi ) HyFlow is a modeling & simulation formalism driven by expressiveness and performance analysis. We present (pi ) HyFlow semantics, and several applications to illustrate (pi ) HyFlow ability to describe a diversity of systems.

This paper addresses the problem of active diagnosis in Timed Event Graphs for the localization of time failures. Active diagnosis is the process of controlling the system in order to refine a previous diagnosis. A first algorithm is proposed which sets up a multi-input control policy that ensures that the system’s observable response is informative enough to identify the source of the delay more precisely, with an analysis of the propagation paths through the TEG. A second algorithm extends the first one to improve the performance of the localization by adding a specific method to analyze the effect of circuits when a time failure propagates.

The Conflict-Free Electric Vehicle Routing Problem (CF-EVRP) is a combinatorial optimization problem of designing routes for vehicles to execute tasks such that a cost function, typically the number of vehicles or the total travelled distance, is minimized. The CF-EVRP involves constraints such as time windows on the tasks’ execution, limited operating range of the vehicles, and limited capacity on the number of vehicles that a road segment can simultaneously accommodate. In previous work, the compositional algorithm ComSat was introduced to solve the CF-EVRP by breaking it down into sub-problems and iteratively solve them to build an overall solution. Though ComSat showed good performance in general, some problem instances took significant time to solve due to the high number of iterations required to find solutions for two sub-problems, namely the Routing Problem, and the Paths Changing Problem. This paper addresses the bottlenecks of ComSat and presents new formulations for both sub-problems in order to reduce the number of iterations required to find feasible solutions to the CF-EVRP. Experiments on sets of benchmark instances show the effectiveness of the presented improvements.

This work proposes a mathematical programming (MP) representation of discrete event simulation of timed Petri nets (TPN). Currently, mathematical programming techniques are not widely applied to optimize discrete event systems due to the difficulty of formulating models capable to correctly represent the system dynamics. This work connects the two fruitful research fields, i.e., mathematical programming and Timed Petri Nets. In the MP formalism, the decision variables of the model correspond to the transition firing times and the markings of the TPN, whereas the constraints represent the state transition logic and temporal sequences among events. The MP model and a simulation run of the TPN are then totally equivalent, and this equivalence has been validated through an application in the queuing network field. Using a TPN model as input, the MP model can be routinely generated and used as a white box for further tasks such as sensitivity analysis, cut generation in optimization procedures, and proof of formal properties.