Discrete dynamic optimization of N-stages control for isolated signalized intersections

The N-stages control problem for isolated signalized intersections is defined as the control problem to disperse initial queue lengths to their optimal steady-state values in N cycles. Based on a discrete-event model of a simplified isolated signalized intersection, the N-stages control problem is formulated as a linear programming problem as well as a quadratic programming problem. A new algorithm is proposed for solving the discrete optimization problem by simple calculations, based on the optimal solution of the corresponding continuous-time problem. Numerical comparisons between the continuous-time optimal solution and the discrete-event optimal solutions, obtained from linear programming and sequential quadratic programming, are given for a few examples.     

TIME WINDOWS: AUTOMATED ABSTRACTION OF CONTINUOUS-TIME MODELS INTO DISCRETE-EVENT MODELS IN HIGH AUTONOMY SYSTEMS∗

This paper describes the automated generation of time windows from continuous system simulation models. Time windows can be used to automatically generate equivalent discrete-event models at a coarser granularity level and they are instrumental to the design of event-based control systems. The generation of time windows represents one facility in the knowledge-based multifacetted modeling and simulation environment. DEVS-Schemc. In this environment, continuous-time and discrete-event models can coexist and they can be amalgamated with AI techniques. The usefulness of these concepts will be demonstrated by means of a model of a robot controlled fluid handling laboratory for Space Station Freedom to be used for research in Life Sciences, Microgravity Sciences, and Space Medicine.     

Event-driven receding horizon control for energy-efficient container handling

The performance of container terminals needs to be improved to adapt the growth of containers while maintaining sustainability. This paper provides a methodology for determining the trajectory of interacting machines that transport containers between the quayside area and the stacking area in an automated container terminal. The behaviors of the interacting machines are modeled as a combination of discrete-event dynamics and continuous-time dynamics. An event-driven receding horizon controller (RHC) is proposed for achieving energy efficient container handling. The underlying control problems are hereby formulated as a collection of small optimization problems that are solved in a receding horizon way. Simulation studies illustrate that energy consumption of container handling can indeed be reduced by the proposed methodology. Moreover, an assessment is made of performance of the proposed RHC controller under different types of uncertainties.     

Statistical probabilistic model checking with a focus on time-bounded properties

Probabilistic verification of continuous-time stochastic processes has received increasing attention in the model-checking community in the past five years, with a clear focus on developing numerical solution methods for model checking of continuous-time Markov chains. Numerical techniques tend to scale poorly with an increase in the size of the model (the “state space explosion problem”), however, and are feasible only for restricted classes of stochastic discrete-event systems. We present a statistical approach to probabilistic model checking, employing hypothesis testing and discrete-event simulation. Since we rely on statistical hypothesis testing, we cannot guarantee that the verification result is correct, but we can at least bound the probability of generating an incorrect answer to a verification problem.     

Simulation modelling and analysis of part and tool flow control decisions in a flexible manufacturing system

This paper presents the details of a simulation study carried out for analyzing the impact of scheduling rules that control part launching and tool request selection decisions of a flexible manufacturing system (FMS) operating under tool movement along with part movement policy. Two different scenarios have been investigated with respect to the operation of FMS. In scenario 1, the facilities such as machines, tool transporter and part transporter are assumed to be continuously available without breakdowns, whereas in scenario 2, these facilities are prone to failures. For each of these scenarios, a discrete-event simulation model is developed for the purpose of experimentation. A number of scheduling rules are incorporated in the simulation models for the part launching and tool request selection decisions. The performance measures evaluated are mean flow time, mean tardiness, mean waiting time for tool and percentage of tardy parts. The results obtained through the simulation have been statistically analyzed. The best possible scheduling rule combinations for part launching and tool request selection have been identified for the chosen FMS.     

An implementation method for the supervisory control of time-driven systems applied to high-voltage direct current transmission grids

In recent years, the growth of renewable energy production has encouraged the development of new technologies, such as High-Voltage Direct Current (HVDC) networks, that enhance the integration of such energy sources to power transmission grids. However, this type of technology introduces new challenges in the way power transmission systems are controlled and operated, as faster and more complex control strategies will be needed in a domain which nowadays relies heavily on human decisions. In this context, Discrete Event Systems (DES) modeling and Supervisory Control Theory (SCT) are powerful tools for the development of a supervisory control to be deployed in the grid. This paper presents an application of the SCT to HVDC grids and proposes an implementation method for the resulting supervisors. The proposed method is capable of integrating decentralized and discrete-event controllers that interact with the continuous-time physical system. The language chosen for the implementation is C code, as it can be easily incorporated in power system simulation software, such as EMTP-RV. The method is validated by the simulation of the start-up of a point-to-point link in the EMTP-RV software.     

Infinitesimal Perturbation Analysis in Networks of Stochastic Flow Models: General Framework and Case Study of Tandem Networks with Flow Control

This paper presents a general algorithmic framework for computing the IPA derivatives of sample performance functions defined on networks of fluid queues. The underlying network-model consists of bi-layered hybrid dynamical systems with continuous-time dynamics at the lower layer and discrete-event dynamics at the upper layer. The linearized system, computed from the sample path via a discrete-event process, yields fairly simple algorithms for the IPA derivatives. As an application-example, the paper discusses loss and workload performance functions in a tandem network with congestion control, subjected to signal delays.     

基于Agent的空中交通系统建模与仿真研究

从系统特性、内在运行机制和外在行为表现等方面对空中交通系统进行了深入分析,提出基于离散事件和连续时间相结合的混合空中交通仿真模型。该模型采用Agent技术表现实现个体微观行为的仿真,集成个体微观行为构成系统宏观性能表现。构建了典型的空中交通系统的Agent模型：飞机Agent和管制员Agent。最后,通过一个起飞和落地的应用验证了基于Agent的空中交通混合仿真在模拟个体微观行为和系统宏观表现方面均具有较高的逼真度。     

A Message-Based Approach to Discrete-Event Simulation

This paper develops a message-based approach to discrete-event simulation. Although message-based simulators have the same expressive power as traditional discrete-event simulation lanuages, they provide a more natural environment for simulating distributed systems. In message-based simulations, a physical system is modeled by a set of message-communicating processes. The events in the system are modeled by message-communications. The paper proposes the entity construct to represent a message-communicating process operating in simulated time. A general wait until construct is used for process scheduling and message-communication. Based on these two notions, the paper proposes a language fragment comprising a small set of primitives. The language fragment can be implemented in any general-purpose, sequential programming language to construct a message-based simulator. We give an example of a message-based simulation language, called MAY, developed by implementing the language fragment in Fortran. MAY is in the public domain and is available on request.     

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.     

A process algebra based simulation model of a miniload-workstation order picking system

A modular discrete-event simulation model for a miniload-workstation (ML-WS) order picking system has been developed using a process algebra based simulation language. The proposed model is structured systematically such that distinctions between areas and operational layers can be clearly identified. Furthermore, subsystems and decentralized controls are applied in the model architecture. We demonstrate the modularity of the model by experiments, in which some control heuristics and the number of miniloads are altered. A realistic, industrial scale distribution center is used as the reference case for the simulation study. The resulting model architecture allows easy implementation of various system structures, design parameters, and control heuristics.     

On the supremal controllable sublanguage in the discrete-eventmodel of nondeterministic hybrid control systems

This paper is concerned with the logical control of hybrid control systems (HCS). It is assumed that a discrete-event system (DES) plant model has already been extracted from the continuous-time plant. The problem of hybrid control system design can then be solved by applying logical DES controller synthesis techniques to the extracted DES plant. Traditional DES synthesis methods, however, are not always applicable since the extracted plant DES will often exhibit nondeterministic transitions. This paper presents an extension of certain DES controller synthesis techniques to the nondeterministic control automaton found in HCS. In particular, this paper derives a formula computing the supremal controllable sublanguage of a given specification language under the assumption that the DES plant exhibits nondeterministic transitions     

离散事件系统规范DEVS研究

离散事件系统是一类常见的系统，如何对这类系统进行描述与建模是离散事件系统仿真研究的核心内容。离散事件系统规范DEVS是一种离散事件系统形式化描述方法，它具有层次化和模块化的特点，利用该方法可对复杂的离散事件系统进行建模、设计、分析和仿真。该文详细介绍了DEVS基本模型和耦合模型，给出了DEVS在耦合运算下的封闭性构造证明，并提出了一种具有嵌套层次结构的DEVS耦合模型实现算法，该算法对基于DEVS描述的离散事件系统的仿真实现具有一定参考价值。     

Controllability and control-invariance in discrete-event systems

Recently, for discrete-event systems modelled by automata, Ramadge and Wonham (1987 a, b) have proposed two control techniques called ‘supervisory control’ and ‘state feedback logic’. If control specifications are given in terms of predicates on the set of states, both techniques are applicable. This paper discusses the relationship between these techniques. It is shown that the language accepted by the discrete-event system with maximally permissive feedback is equal to the supremal controllable language if the predicate is control invariant. Moreover, it is shown that the predicate is control invariant if there exists a controllable language with a certain condition on the set of reachable states, but the converse does not hold in general     

Language-measure-theoretic optimal control of probabilistic finite-state systems

Supervisory control theory for discrete event systems, introduced by Ramadge and Wonham, is based on a non-probabilistic formal language framework. However, models for physical processes inherently involve modelling errors and noise-corrupted observations, implying that any practical finite-state approximation would require consideration of event occurrence probabilities. Building on the concept of signed real measure of regular languages, this paper formulates a comprehensive theory for optimal control of finite-state probabilistic processes. It is shown that the resulting discrete-event supervisor is optimal in the sense of elementwise maximizing the renormalized langauge measure vector for the controlled plant behaviour and is efficiently computable. The theoretical results are validated through several examples including the simulation of an engineering problem.     

Active diagnosis of discrete-event systems

The need for accurate and timely diagnosis of system failures and the advantages of automated diagnostic systems are well appreciated. However, diagnosability considerations are often not explicitly taken into account in the system design. In particular, design of the controller and that of the diagnostic subsystem are decoupled, and this may significantly affect the diagnosability properties of a system. The authors present an integrated approach to control and diagnosis. More specifically, they present an approach for the design of diagnosable systems by appropriate design of the system controller. This problem, which they refer to as the active diagnosis problem, is studied in the framework of discrete-event systems (DESs); it is based on prior and new results on the theory of diagnosis for DESs and on existing results in supervisory control under partial observations. They formulate the active diagnosis problem as a supervisory control problem where the legal language is an “appropriate” regular sublanguage of the regular language generated by the system. They present an iterative procedure for determining the supremal controllable, observable, and diagnosable sublanguage of the legal language and for obtaining the supervisor that synthesizes this language. This procedure provides both a controller that ensures diagnosability of the closed-loop system and a diagnoser for online failure diagnosis. The procedure can be implemented using finite-state machines and is guaranteed to converge in a finite number of iterations. The authors illustrate their approach using a simple pump-valve system     

Hybrid system modeling using the SIMANLib and ARENALib Modelica libraries

The ARENALib and SIMANLib Modelica libraries replicate the basic functionality of the Arena simulation environment and the SIMAN language. These libraries facilitate describing discrete-event models using the Arena modeling methodology. ARENALib and SIMANLib models can be combined with other Modelica models in order to describe complex hybrid systems (i.e., combined continuous-time and discrete-event systems). The implementation and design of SIMANLib and ARENALib is discussed. The ARENALib components have been built in a modular fashion using SIMANLib. The SIMANLib components have been described as Parallel DEVS models and implemented using DEVSLib, a Modelica library previously developed by the authors to support the Parallel DEVS formalism. The use of Parallel DEVS as underlying mathematical formalism has facilitated the development and maintenance of SIMANLib. The modeling of two hybrid systems is discussed to illustrate the features and use of SIMANLib and ARENALib: firstly, a soaking-pit furnace; secondly, the malaria spread and an emergency hospital. DEVSLib, SIMANLib and ARENALib can be freely downloaded from http://www.euclides.dia.uned.es/.