The control of discrete event systems

A discrete event system (DES) is a dynamic system that evolves in accordance with the abrupt occurrence, at possibly unknown irregular intervals, of physical events. Such systems arise in a variety of contexts ranging from computer operating systems to the control of complex multimode processes. A control theory for the logical aspects of such DESs is surveyed. The focus is on the qualitative aspects of control, but computation and the related issue of computational complexity are also considered. Automata and formal language models for DESs are surveyed     

A GSMP formalism for discrete event systems

A precise mathematical framework for the study of discrete event systems is described. The idea is to define a particular type of stochastic process, called a generalized semi-Markov process (GSMP), which captures the essential dynamical structure of a discrete event system. An attempt is also made to give the flavor of the qualitative theory and numerical algorithms that can be obtained as a result of viewing discrete event systems as GSMPs. Likelihood ratio concepts for importance sampling are briefly described     

Distributed simulation of discrete event systems

An overview of distributed simulation of discrete event systems and the issues associated with it. Alternative approaches for decomposing the simulation into tasks that can be run on separate processors are described, and the potential parallelism associated with certain kinds of decomposition is studied. Existing synchronization algorithms are discussed. An attempt is made throughout to show what decomposition approaches and synchronization algorithms may be appropriate depending on properties of the application and the multiprocessor architecture. Empirical and analytical performance studies are described, where available     

Stochastic optimization of discrete event systems simulation

The Score Function (SF) method has been proposed to estimate the gradient of a performance measure with respect to some continuous parameters in a stochastic system. In this paper we experiment with the use of this estimate in a stochastic approximation algorithm to perform a single-run optimization. The experiment is done on a simple M/M/1 queue. The performance measure involves the average system time per customer at steady-state, and the decision variable is the service rate. The optimal solution is easy to compute analytically, which facilitates the evaluation of the algorithm. Combined with appropriate variance reduction techniques, the method has been shown to be effective in the test problem.We study the algorithm's properties and examine the validity of the estimates based on this single run procedure by performing some experimental studies. Implementation “details” necessary for packaging this method with existing simulation software are provided. Finally, there is a set of recommended directions for future research.     

Cross-coupled fuzzy logic control for multiaxis machine tools

This paper presents a design and implementation case study that focuses on contour control of a biaxial CNC machine tools. Since, it is difficult to obtain an accurate nonlinear mathematical model of cross-coupled multiaxis machine tools, here we investigate an alternative to conventional approaches where we employ crosscoupled fuzzy logic controllers for improving the contouring accuracy of multiaxis CNC machine tools. A new fuzzy rule-generated method which is based on a performance index of the contour error obtained from an on-line estimation algorithm is proposed. An adapted output scale factor is adopted to improve the system performance. Experimental results have shown that the desired contouring accuracy can be achieved, and the proposed approach outperforms over uncoupled approaches. In conventional control, increasing contour feedrate for productivity may result in larger contour errors. However, the experimental results have shown that the performance of the proposed approach is still quite good with increasing contour feedrate.     

Goal-seeking problem in discrete event systems simulation

For most complex stochastic systems such as microelectronic systems, the Mean Time To Failure (MTTF) is not available in analytical form. We resort to Monte-Carlo Simulation (MCS) to estimate MTTF function for some specific values of underlying density function parameter(s). MCS models, although simpler than a real-world system, are still a very complex way of relating input parameter(s) to MTTF. This study develops a polynomial model to be used as an auxiliary to a MCS model. The estimated metamodel is a Taylor expansion of the MTTF function in the neighborhood of the nominal value for the parameter(s). The Score Function methods estimate the needed sensitivities (i.e. gradient, Hessian, etc.) of the MTTF function with respect to the input parameter in a single simulation run. The explicit use of this metamodel is the target-setting problem in Taguchi's product design concept: given a desired target MTTF value, find the input parameter(s). A stochastic approximation algorithm of the Robbins-Monro type uses a linear metamodel to estimate the necessary controllable input parameter within a desired accuracy. The potential effectiveness is demonstrated by simulating a reliability system with a known analytical solution.     

Fundamental matrix of discrete singular systems

The objective of this paper is to make clear the fundamental importance of thefundamental matrix ? _k in the analysis of linear discrete-time singular systems. We relate? _k to the coefficientsR _k of the adjoint matrix (zE-A)^?1, find an autoregressive recursion for the? _k , and give the solution of the singular semistate equation in terms of? _k . Also discussed are thesemistatetransition matrix and the singular systemTschirnhausen polynomials. We close by giving a stable numerical technique for the computation of the sequence? _k that is based on first taking the pencilzE-A to triangular form.     

Sample path properties of timed discrete event systems

The basic problem of constructing a perturbed sample path (given a parameter perturbation) from information contained in a nominal sample path is considered. Two conditions, observability and constructability, which have to be satisfied for this to be feasible are identified. One approach for accomplishing this task is to develop an augmented system model which captures both nominal and perturbed system behaviour. For the case of systems with Markov properties, an explicit methodology is presented for constructing such models. It is also shown that by an observability transformation it is generally possible to satisfy constructability conditions allowing the performance of a perturbed discrete event system to be estimated by observing only a nominal sample path. In practice, a variety of techniques may be used to accomplish this goal, depending on issues such as parameter value availability and convergence speed of various performance sensitivity, estimates     

Generic discrete–continuous simulation model for accurate validation in heterogeneous systems design

Heterogeneous systems combining several technologies will potentially overcome several performances and applicability limitations, as well as providing new useful features. However, their design is currently confronted to important challenges. One of the key challenges is the integration of pre-built components specific to different application domains (e.g. electrical, mechanical, optical, etc.). In this context, new CAD tools are mandatory to offer a global view of the designed systems and to enable their overall validation. This paper presents a generic discrete–continuous simulation model for an accurate global validation in heterogeneous systems design. This model enables to use powerful tools for the discrete and continuous domains. Solutions are proposed for model's layers implementation in the case of SystemC and Simulink simulators. The continuous–discrete simulation tool is proposed. This tool integrates the two previous simulators by automatically generating global simulation model instances. The evaluation of the simulation model was performed using an illustrative application.     

Automated control synthesis for an assembly line using discrete event system control theory

The design of logic controllers for event-driven systems continue to rely largely on intuitive methods rather than on formal techniques. This approach results in a control code that requires extensive verification, is hard to maintain and modify, and may even fail at times. Supervisory control theory (SCT) provides a formal approach to logic control synthesis. In order to demonstrate the usefulness of the supervisory control theory in manufacturing systems, an educational test-bed that simulates an automated car assembly line has been built using LEGO/spl reg/ blocks. Finite state machines (FSMs) are used for modeling operations of the assembly line, and for the specifications that accomplish the task of successfully completing the assembly repeatedly. Using the technique of SCT, we derive a supervisor that enforces the specifications while offering the maximum flexibility of assembly. Subsequently a controller is extracted from the maximally permissive supervisor for the purpose of implementing the control by selecting, when possible, at most one controllable event from among the ones allowed by the supervisor. Testing to check the correctness of the control code is reduced, since the controller is guaranteed to enforce the specifications.     

基于单片机控制的自动松果采摘机设计

松果树的枝干比较高,因此果农在进行采摘的时候存在很大的困难并且会耗费很多的劳动力。因此,本文设计了一种针对单片机控制的松果采摘机的自动控制的系统。这种摘机不但可以高效并且快速的对松果进行采摘,同时还能够在对松果保持完好的前提下选择非常好的保护措施,使用人工去进行配合,可以进行自动的寻找和采摘,并且将松果送回等相关的控制动作。     

Introduction to special issue on dynamics of discrete event systems

An overview of discrete-event dynamic system (DEDSs) is given, explaining what they are and discussing their modeling. The types of models are outlined, and factors to be taken into account in modeling are examined. They are: the discontinuous nature of discrete events; the continuous nature of most performance measures; the importance of probabilistic formulation; the need for hierarchical analysis; the presence of dynamics; and the feasibility of the computational burden. It is stressed that DEDS research must include experiment as well as theory     

Adaptive quasi-sliding-mode tracking control for discrete uncertaininput-output systems

In this paper, a discrete robust adaptive quasi-sliding-mode tracking controller is presented for input-output systems with unknown parameters, unmodeled dynamics, and bounded disturbances. The robust tracking controller is comprised of adaptive control and a sliding-mode-based control design. The bounded motion of the system around the sliding surface and the stability of the global system in the sense that all signals remain bounded are guaranteed. The adaptive algorithm, in which the deadzone method is employed even though the upper and lower bounds of the disturbances are unknown, is the extension of the authors' previous work for the state-space systems. An example and its simulation results are presented to illustrate the proposed approach     

基于单片机的汉语教学机的设计

针对目前语文教学设备落后的现状,利用现代电子技术,使用单片机、大容量NAND Flash存储器和LED显示屏等设计出适合小学低年级语文教学使用的汉语教学机.该机能进行汉语拼音、普通话音节、词组和课文的教学.大容量NAND Flash存储器里存储的内容与教材一致,能有效地提高语文教学的效率和效果,特别是该机特有的汉字笔顺的显示功能,对学生汉字书写的规范性有极大的帮助.     

Separation of estimation and control for discrete time systems

An attempt is made to coordinate the numerous results relating to separation of estimation and control in discrete time stochastic control theory. The results vary widely depending upon the assumptions about linearity, criteria, information pattern, constraints, and noise distributions. Some of the less well-known underlying concepts are discussed with the help of a fairly general model.     

Optimal parameter surfaces for 2nd-order discrete control systems

Based on a minimum i.t.a.e. criterion, optimal control algorithm parameter surfaces are presented for 2nd-order computer-controlled systems. They illustrate the variation in proportional, integral and derivative parameters with sampling period, time delay and system time constant.     

New gate model for the transient analysis of logic systems

An extension of the graphical technique for the propagation of signals through logic systems is proposed. Nonlinearities-and transport delays are catered for, and the gate model used is simple and suited to calculation in large systems. A system is examined graphically and the results are compared with those obtained experimentally.     

印刷机张力控制系统设计

基于印刷行业张力控制原理,分析了张力控制系统组成,并介绍了以STM32为主控芯片及外围电路开发而成的闭环张力控制系统,该系统不仅控制精度高,响应速度快,而且操作简单,有合理的PID控制功能,适用于多种印刷材料。它还可以计算出材料筒的直径,使整个张力控制过程更为合理。     

Distributed discrete event simulation for communication networks

A survey of the techniques used in distributed discrete event simulation is presented. Some of the algorithms that have been developed to overcome some of the inherent problems of simulating on distribution systems are then described. The application of distributed discrete event simulation to the performance evaluation of communication networks is addressed. The design and implementation of the DISDESNET (distributed discrete event simulation of networks) simulation package for the simulation of general communication networks is described. Results of tests performed on different configurations are examined and found to demonstrate the flexibility of the package