Discrete-event Behavior Research Articles

A multiagent systems with Petri Net approach for simulation of urban traffic networks

This paper presents a novel model framework for complex urban traffic systems based on the interconnection of a dynamical multi-agent system in a macroscopic level. The agents describe all the types of street segments, intersections, sources and sinks of cars, modelling the behavior of the flow of vehicles through them as simple differential equations. These agents include the phenomena of changes in the flow rate due to congestions, traffic signals and the density of the vehicles. Traffic signal changes are obtained by the evolution of Petri Nets, in order to represent a more real behavior. Therefore, a complex network can be constructed by the interconnection of the agents, in continuous time, and the Petri Nets, in a discrete-event behavior, becoming a hybrid and scalable system. In order to analyze the performance of the approach, a real set of streets and intersections in Montevideo City is studied. Also, the approach is compared with a simulation realized in the software TSIS-CORSIM, which contains real data of density of vehicles. The multi-agent system achieves comparable results, taking into account the differences in the level of details respect to TSIS-CORSIM. Thus, the results can represent the most important issues of vehicular traffic with less computational resources.

Model properties for efficient synthesis of nonblocking modular supervisors

Supervisory control theory provides means to synthesize supervisors for systems with discrete-event behavior from models of the uncontrolled plant and of the control requirements. The applicability of supervisory control theory often fails due to a lack of scalability of the algorithms. This paper proposes a format for the requirements and a method to ensure that the crucial properties of controllability and nonblockingness directly hold, thus avoiding the most computationally expensive parts of synthesis. The method consists of creating a control problem dependency graph and verifying whether it is acyclic. Vertices of the graph are modular plant components, and edges are derived from the requirements. In case of a cyclic graph, potential blocking issues can be localized, so that the original control problem can be reduced to only synthesizing supervisors for smaller partial control problems. The strength of the method is illustrated on two case studies: a production line and a roadway tunnel.

Event-driven industrial robot control architecture for the Adept V+ platform.

Modern industrial robotic systems are highly interconnected. They operate in a distributed environment and communicate with sensors, computer vision systems, mechatronic devices, and computational components. On the fundamental level, communication and coordination between all parties in such distributed system are characterized by discrete event behavior. The latter is largely attributed to the specifics of communication over the network, which, in terms, facilitates asynchronous programming and explicit event handling. In addition, on the conceptual level, events are an important building block for realizing reactivity and coordination. Event-driven architecture has manifested its effectiveness for building loosely-coupled systems based on publish-subscribe middleware, either general-purpose or robotic-oriented. Despite all the advances in middleware, industrial robots remain difficult to program in context of distributed systems, to a large extent due to the limitation of the native robot platforms. This paper proposes an architecture for flexible event-based control of industrial robots based on the Adept V+ platform. The architecture is based on the robot controller providing a TCP/IP server and a collection of robot skills, and a high-level control module deployed to a dedicated computing device. The control module possesses bidirectional communication with the robot controller and publish/subscribe messaging with external systems. It is programmed in asynchronous style using pyadept, a Python library based on Python coroutines, AsyncIO event loop and ZeroMQ middleware. The proposed solution facilitates integration of Adept robots into distributed environments and building more flexible robotic solutions with event-based logic.

Feedback Control of Cluster Tools for Regulating Wafer Delays

Robotized cluster tools for semiconductor manufacturing have strict time constraints such that a wafer processed at a processing chamber should be unloaded within a specified time limit. Otherwise, it has a serious quality problem due to residual gases and heat within the chamber. Even though there have been studies on identifying a feasible tool operation schedule over such time constraints on wafer delays, such a schedule is subject to timing disruptions or time variation, and thus may violate the time constraints. In this study, we propose a more robust method of regulating wafer delays against timing disruptions not to exceed a specified limit. We first model the discrete-event behavior of a tool by a timed event graph. We then develop a feedback controller for single-armed and dual-armed cluster tools that can satisfy the time constraints by regulating wafer delays. To do this, we develop a feedback controller for the timed event graph by analyzing the timing behavior in a linear system model based on the max-plus algebra. The feedback controller postpones an event or firing of a transition, i.e., loading a wafer into a chamber, until a properly determined time elapses after an associated preceding event occurs. Finally, we present examples of feedback control and show that the feedback control is quite robust even under persistent time variation.

Design of Discrete–Event Controllers for Flexible Manufacturing System using Informal Product Requirements

Abstract This approach collects informal product requirements (customer needs), determines the highest hierarchical functional requirement (FR) for a product to satisfy the stated needs and generates the corresponding recipe procedure for a coordination level of a flexible manufacturing cell. Then, an axiomatic system design methodology is applied to decompose hierarchically the FR and to generate a corresponding design parameter (DP) for each FR. DP are components able to enable–disable their respective FR to generate an acceptable process cell operational sequence that represents the “functional specifications” of the manufacturing process. Thus, a discrete–event system class of controllers for flexible manufacturing system can be constructed using the output of the axiomatic design methodology to built “elementary components” that contains the discrete-event behaviour of the functional specifications. These elementary components are the building blocks of the “open-loop model” from which the discrete–event controller is synthesized for the coordination control layer. Finite state machines (FSM) are extended to state–labelled to facilitate the detection of behaviour properties and forbidden states. An example of the approach is presented; a customer requires the design of some similar products and their respective processes. The example emphasizes the structured design process.

A computational model of time for stiff hybrid systems applied to control synthesis

Computation has quickly become of paramount importance in the design of engineered systems, both to support their features as well as their design. Tool support for high-level modeling formalisms has endowed design specifications with executable semantics. Such specifications typically include not only discrete-time and discrete-event behavior, but also continuous-time behavior that is stiff from a numerical integration perspective. The resulting stiff hybrid dynamic systems necessitate variable-step solvers to simulate the continuous-time behavior as well as solver algorithms for the simulation of discrete-time and discrete-event behavior. The combined solvers rely on complex computer code which makes it difficult to directly solve design tasks with the executable specifications. To further leverage the executable specifications in design, this work aims to formalize the semantics of stiff hybrid dynamic systems at a declarative level by removing implementation detail and only retaining ‘what’ the computer code does and not ‘how’ it does it. A stream-based approach is adopted to formalize variable-step solver semantics and to establish a computational model of time that supports discrete-time and discrete-event behavior. The corresponding declarative formalization is amenable to computational methods and it is shown how model checking can automatically generate, or synthesize, a feedforward control strategy for a stiff hybrid dynamic system. Specifically, a stamper in a surface mount device is controlled to maintain a low acceleration of the stamped component for a prescribed minimum duration of time.

Towards Computational Hybrid System Semantics for Time-Based Block Diagrams

At the core of Model-Based Design, computational models have caused an autocatalytic trend to use computation in design by unlocking the potential of model transformations. Precisely specifying a computational transformation requires well-defined semantics of the source and target representations. In this regard, continuous-time behavior is an essential aspect of time-based block diagrams that is typically approximated by numerical integration. The corresponding theory, however, is mostly concerned with local error and the mathematical semantics of long time behavior fails to be sufficiently precise from a computational perspective. In this work, first a computational semantics is developed based on a multi-stage variablestep solver. Next, the computational semantics of the discrete and continuous parts of hybrid systems and their interaction are formalized in a unifying framework. The framework exploits a successful functional approach to defining discrete-time and discrete-event behavior established in other work. Unification is then achieved by developing a computational representation of the continuous-time behavior as pure functions on streams.

Systematic supervisory control solutions for under-load tap-changing transformers

Discrete-event systems (DES) can be found as essential integrated subsystems in many complex systems, e.g. electrical power systems. Under-load tap-changing (ULTC) transformers which obviously have discrete-event behavior are widely used in transmission systems to take care of instantaneous variations in the load conditions in substations. In this paper, the voltage control problem in ULTC is solved in different modes of operation, using DES-based solutions. These solutions include: DES supervisory control, timed DES supervisory control and a hierarchical structure for the control system. It is shown that the specifications are controllable and the closed-loop control system is non-blocking.

Zero-Crossing Location and Detection Algorithms For Hybrid System Simulation

Computational models of embedded control systems often combine continuous-time with discrete-event behavior, mathematically representing hybrid dynamic systems . An essential element of numerical simulation of a hybrid dynamic system is the generation of discrete events from continuous variables that exceed thresholds. In particular, the occurrence of such an event has to be detected and the point in time where the threshold is first exceeded has to be located . This paper presents a number of problems that are encountered in event detection and location when using existing techniques. Solution strategies that balance efficiency and robustness are presented to address: (i) repeated detection of a zero-crossing event at consecutive time steps, (ii) masked zero-crossing events because of multiple zero-crossing functions, and (iii) chattering and Zeno behavior.

On the Use of UML for Modeling Mechatronic Systems

This paper describes a modeling language that aims to provide a unified framework for representing control systems, namely, physical plants coupled with computer-based control devices. The proposed modeling methodology is based on the cardinal principle of object orientation, which allows describing both control software and physical components using the same basic concepts, particularly those of capsules, ports, and protocols. Furthermore, it is illustrated how the well-known object-oriented specification language unified modeling language can be adopted, provided an adequate formalization of its semantics, to describe structural and behavioral aspects of control systems, related to both logical and physical parts. Note to Practitioners-The development of an automated system within an industrial setting is a complex task, whose successful result depends on the joint efforts of a team of designers with different scientific backgrounds and specialized knowledge. In fact, an automated system is typically composed of a mechanical assembly, which must be precisely designed and manufactured, and a set of sensors and actuators (e.g., electrical drives, pneumatic systems, etc.), which are, on their turn, controlled most of the time by means of digital processors. Of course, both electrical parts and control algorithms (e.g., proportional, integral, and derivative (PID) regulators, logic and supervisory control, reference trajectories for mechanical motions, etc.) should be designed with the same care given to mechanical aspects. Moreover, it is undeniable that none of the various parts composing the automated system design specification can, on their own, allow engineers to understand the actual behavior of the whole system, especially without a common description language that is understandable for all of the designers. The present paper introduces a unified language which aims to support integrated design specifications of automated systems, including the dynamics of heterogeneous physical assemblies, the discrete-event behavior of distributed control software, and the specification of interface ports between the plant and the control system. With the proposed language, it is possible to obtain a complete picture of the automated system suitable for its simulation, documentation, and validation. The modeling language described in the paper supports the principles of object orientation. This choice moves in the direction of enhancing modularity and reusability properties of design specifications, which are aspects of great importance in the design practice. Moreover, the object-oriented approach to automated systems design proposed in the paper aims to introduce the concept of "design by extension" in the manufacturing industry. This means that the definition of specialization relationships between classes of components implies that those components should be designed in order to be substitutable with each other, especially from a dynamic point of view. This aspect will be the subject of further papers illustrating other practical insights on the use of object-oriented models for automated systems

Analytical approach to evaluate language measure parameters for discrete-event supervisory control

The discrete-event dynamic behaviour of physical plants is usually represented by regular languages that can be realized as deterministic finite state automata (DFSA). The concept and construction of signed real measure of regular languages have been recently developed in literature. The language measure is assigned two parameters, namely a state transition cost matrix and a state cost vector. This article formulates an analytical approach to determine the language measure parameters. The proposed approach is based on the theory of Markov stochastic processes. The DFSA of the discrete-event dynamic behaviour is first transformed into a Markov chain. Therefore, an event cost is calculated by the occurrence probability of this event in a given state of a discrete-time Markov chain. The determination of the state cost vector is based on the underlying continuous-time Markov chain to evaluate the steady state-state probabilities. Kronecker algebra is used to facilitate the description of large systems, while minimizing memory requirements. It is shown, through a manufacturing example, how the formulated method may provide a systematic way for quantitative evaluation and comparison of the discrete-event dynamic behaviour of the supervised plants.

Modelling risks in supply chains using Petri net approach

In supply chains, risk analysis involves the process of identifying threats and system vulnerabilities to determine consequences and estimate the expected loss. To analyse any risk environment, it is vital to know the paths of threat and the probability associated with each. Therefore, a complete structure and inference engine are required to determine the most probable path and the relative probabilities of occurrence for any chain of events. Petri Nets (PNs) are considered best to model the discrete event system. This paper introduces a novel approach that uses PNs to model the discrete event behaviour of supply chains and incorporates the max–min inferencing method used in fuzzy reasoning to incorporate the subjective probabilities of events associated with the supply chain process. The proposed approach generates its model based on matrices and performs inferencing automatically. The proposed model uses subjective probability thresholds based on military (MIL) standards and can derive risk analysis results under a changing environment.

Verifying Collaborative Behavior in Component-Based DEVS Models

Construction of models from reusable components requires clear and precise understanding of design and integration dependencies. Formalization of the semantics of such dependencies is a prerequisite for reasoning about compositional consistency. DEVS formalism provides a sound and powerful framework under which discrete event behavior and component coupling can be precisely defined. Reasoning about the interaction behavior of components to ensure that they are coordinated around specific collaboration constraints is a serious problem inherent in coupled DEVS models. At least two major complications arise: (1) analytically identifying components that violate required interaction constraints is difficult, and (2) the evolution and substitution of new participants in coupled models give rise to unanticipated behavioral conflicts. This article presents a solution technique that addresses both of these problems. Local consistency conditions are formalized, and decidable inference mechanisms are developed to facilitate determining the compositional consistency and safe refinement of DEVS models.

Beziehungen zwischen qualitativen dynamischen Modellen und dem Frobenius-Perron-Operator (Connections between Qualitative Dynamical Models and the Frobenius-Perron Operator)

AbstractThe paper concerns the discrete-event behaviour of quantised systems. As the state can only be measured through a quantiser, trajectory bundles have to be considered, which can be represented for autonomous systems by the Frobenius-Perron operator and for systems with inputs by the Foias operator. These operators can be written down in an explicit form only for a restricted class of systems. Hence, discrete approximations of these operators are used in systems analysis. The paper shows that these approximations are identical to the state transition functions of stochastic automata, which are used in process diagnosis and verification. This interesting connection between results from mathematical systems theory and the literature on hybrid control systems makes it possible to combine the results obtained in both fields.

Hybrid modeling and dynamic simulation of automated batch plants

Abstract A proposal is presented for the hybrid modeling and dynamic simulation of automated batch processing plants with dominant discrete-event behavior. The proposal encompasses current techniques for modeling continuous-time/discrete-event processes, synthesizing discrete-event controllers as well as the use of industrial standards for batch control. The result is a hierarchical-modular model of a plant in which process and control tasks are clearly differentiated. Implementation rules are established for a specific dynamic simulator capable of handling hybrid systems. The approach is demonstrated by building and verifying a complete model for an automated milk pasteurization plant. Results show that handling problems of realistic complexity is feasible using state-of-the-art technology.

EMBEDDED CODE GENERATION FOR EFFICIENT REINITIALIZATION

Embedded control system design involves continuous time, discrete event mode switching, and discontinuities in system behavior and requires support for: (i) continuous behavior, (ii) discrete event behavior, and (iii) re-initialization when discrete events occur. The graphical block diagram formalism that supports continuous behavior modeling is extended by logic components that seamlessly integrate. Re-initialization is supported by state reset ports and state output ports of the integrator component. In addition, the dynamic semantics of a formalism is specified by a computational model. For Matlab-Simulink this consists of a number of interface methods that are called at pre-defined points in the model execution. Automatic generation of efficient embedded code allows the use of high-level modeling formalisms for design and analysis.

Representation of Hybrid Systems by Means of Stochastic Automata

In this paper hybrid systems with discrete-event measurements and inputs are considered. Such systems consist of a continuous-variable subsystem and a discrete-event subsystem which are connected in a closed loop. Stochastic automata are used as models of the discrete-event behavior of the hybrid system, which is in general non-deterministic. It is shown that the model can be set up by, first, modeling the discrete-event behavior of the continuous-variable subsystem by means of a stochastic automaton. It is shown, that the transition relation of this automaton can be derived from a continuous-variable description of the subsystem. Second, the resulting model is combined with the model of the discrete-event subsystem, which in general can be represented by a deterministic automaton. As the continuous-variable subsystem and, therefore, also the hybrid system cannot be modeled exactly by an automaton, the model of the hybrid system generates spurious solutions. Therefore, conditions on the model of the continuous-variable and on the model of the hybrid system will be presented which yield the best complete model of the hybrid system, i.e., the model which generates all event sequences which may occur in the hybrid system and the least number of spurious solutions.

Diagnosis of transient faults in quantised systems

This paper concerns the diagnosis and identification of faults that occur in systems where signals can only be measured through a quantiser. A qualitative model is used that represents the discrete-event behaviour of the quantised system. Three different diagnostic algorithms are presented for determining the fault probabilities, the first concerning faults currently affecting the system and the second determining the probabilities that faults occurred at any time in the past. The third algorithm is based on the assumption that the faults occurred only during a time interval in the past. Due to this assumption, the algorithm is applicable for continuously running processes and for the online identification of transient faults. The approach is illustrated by an example of a manufacturing cell.

Fault Detection of a Diesel Injection System by Qualitative Modelling

The paper presents a method for onboard-diagnosis which combines a model-based diagnostic scheme with a qualitative modelling approach. It is shown how a qualitative model which represents the qualitative, discrete-event behaviour of the system can be set up in a systematic way by abstraction or by qualitative identification. Experimental results are given for the qualitative modelling and fault detection of a Common-Rail diesel injection system.

Process supervision by means of a hybrid model

Abstract The paper concerns process supervision tasks in which a continuous-variable system has to be moved into a globally defined final state. A hybrid model is proposed that describes the discrete-event behaviour as well as the quantitative behaviour of the continuous-variable system. The model consists of a Petri net and of differential equations whose validity depends on the marking of the net. The supervisory control task is solved by searching for a path within the Petri net from the current towards the final state and by using the relevant quantitative models to determine the speed of the state transitions. The results are illustrated by means of a laboratory tank system.