Fabio Balduzzi’s research while affiliated with Polytechnic University of Turin and other places

First-order hybrid Petri nets are models that consist of continuous places holding fluid, discrete places containing a non-negative integer number of tokens, and transitions, either discrete or continuous. In the first part of the paper, we provide a framework to describe the overall hybrid net behaviour that combines both time-driven and event-driven dynamics. The resulting model is a linear discrete-time, time-varying state variable model that can be directly used by an efficient simulation tool. In the second part of the paper, we focus on manufacturing systems. Manufacturing systems are discrete-event dynamic systems whose number of reachable states is typically very large, hence approximating fluid models have often been used in this context. We describe the net models of the elementary components of a flexible manufacturing system (machines and buffers) and we show in a final example how these modules can be put together in a bottom-up fashion.

In this paper we present a novel formulation for analysis and performance optimisation of flexible manufacturing systems. We approximately represent the dynamics of the system with a hybrid model and derive an optimum control strategy for part routing and machine scheduling. We show that the system can be described with a single formalism as a stochastic discrete time, time-varying, state variable model which allows fast and direct design of the system configuration.

In this paper we present a novel approach to the control of manufacturing systems via agent interactions. Based on a decentralized control strategy the agents can collaborate with each other conveniently. We provide a distributed architecture to model the elementary services (an unreliable machine coupled with a finite buffer) in terms of hybrid automata which are co-operating in a manufacturing system, and we show how the agents can efficiently make their control decisions using their local rules.

In this paper, we present a hybrid formulation for the modelling and control of automated manufacturing systems combining both discrete and continuous dynamics. We derive a hierarchical two-level production control policy based on hybrid automata models and capable of providing closed-loop behaviors which satisfy both logic-based and goal optimization specifications. Our main contribution is the integration of fluid approximations within a hybrid automata model aiming at performance optimization subject to logical constraints. By introducing the notion of macro-states and macro-events, we show that these settings can be achieved through a supervisory controller which specifies a desired macro-event trajectory set, represented by a generated language, upon which the optimization procedure is being performed

Describes a hierarchical two level modeling and control framework for real-time manufacturing processes, based on hybrid Petri nets, and capable of integrating monitoring and fault detection techniques along with performance optimization procedures. At the higher level, first-order hybrid Petri nets are used to generate the asynchronous concurrent events characterizing the nominal optimal system behavior, also providing the machine production rates. At the lower level, a real time scheduler and a discrete Petri net communicate with the field-bus devices to force the machine to produce at the rates provided by the upper level, and monitor the occurring events by keeping track of part movements. Whenever a process failure is detected, the diagnosis procedure is triggered, and a recovery sequence is imposed.

In this paper we tackle the decidability of marking reachability for a hybrid formalism based on Petri nets. The model we consider is the untimed version of First{Order Hybrid Petri Nets: it combines a discrete Petri net and a continuous Petri net, the latter being a ∞uid version of a usual discrete Petri net. It is suggested that the decidability results should be pursued exploiting a hierarchy of models as it has been done in the framework of Hybrid Automata. In this paper we deflne the class of Single{Rate Hybrid Petri Nets: the continuous dynamics of these nets is such that the vector of the marking derivatives of the continuous places is constant but for a scalar factor. This class of nets can be seen as the counterpart of timed automata with skewed clocks. We prove that the reachability problem for this class can be reduced to the reachability problem of an equivalent discrete net and thus it is decidable.

We consider in this paper first-order hybrid Petri nets, a model that consists of continuous places holding fluid, discrete places containing a nonnegative integer number of tokens, and transitions, either discrete or continuous. We set up a linear algebraic formalism to study the first-order continuous behavior of this model and show how its control can be framed as a conflict resolution policy that aims at optimizing a given objective function. The use of linear algebra leads to sensitivity analysis that allows one to study of how changes in the structure of the model influence the optimal behavior. As an example of application, we show how the proposed formalism can be applied to flexible manufacturing systems with arbitrary layout and different classes of products

In this paper we discuss a hybrid formulation for the modeling and control of automated manufacturing systems within a framework that distinguishes two levels of aggregation. At the lower level the discrete flows of parts are approximated by first-order fluid models. At the higher level a finite automaton represents the transitions of the system through a sequence of admissible macro-states at the occurrence of the macro-events. We describe both levels with a single formalism by a hybrid automaton and we approach the safety verifcation of the system requirements by addressing the reachability problem in terms of the timing information associated with the verification problem

We discuss a novel formulation for the optimal control of discrete-event dynamic processes representing manufacturing systems characterized by unreliable machines, finite buffers and time-varying predictable demands. We approximately represent the dynamics of the system with a hybrid model and derive an optimum control strategy for parts routing and machines scheduling embedded in a two-levels hierarchical control framework. At the higher level the discrete flows of parts are described by first-order fluid approximations and an optimum receding horizon control policy for the machines production rates is obtained by solving a sequence of linear programming problems. At the lower level a discrete-event real time dispatcher is used to track the solution of the upper level controller as closely as possible