Efficient robust supervisors for discrete event systems

This paper is a sequel to a previous publication by the same authors, in which an efficient modular solution to a robust supervisory control problem for discrete event systems modeled by finite automata with prefix-closed specification languages has been presented. This solution is based on a general recursive robust control scheme, which has been successfully applied to a number of problems. The additional contributions of the present paper are： （a） a slight generalization of the problem assumptions; （b） an alternative derivation of some of the results and an alternative formulation of the controller; （c） a detailed description of a very efficient on-line implementation algorithm; and （d） an illustrative practical example.

Topology-Based and Event-Oriented Approach to Simulation of Cyber-Physical Systems

A simulation model for cyber-physical systems(CPSs)was presented.The model was developed by the method of combination of topology-based and event-oriented that could be used to simulate systems with routing flexibility,service-selection flexibility and service- mode flexibility overall by integrating the strategies related.The validity of the model has been verified by two extensive experiments.

Control of Non-Deterministic Systems With μ-Calculus Specifications Using Quotienting

The supervisory control problem for discrete event system(DES) under control involves identifying the supervisor, if one exists, which, when synchronously composed with the DES,results in a system that conforms to the control specification. In this context, we consider a non-deterministic DES under complete observation and control specification expressed in action-based propositional μ-calculus. The key to our solution is the process of quotienting the control specification against the plan resulting in a new μ-calculus formula such that a model for the formula is the supervisor. Thus the task of control synthesis is reduced a problem of μ-calculus satisfiability. In contrast to the existing μ-calculus quotienting-based techniques that are developed in deterministic setting, our quotienting rules can handle nondeterminism in the plant models. Another distinguishing feature of our technique is that while existing techniques use a separate μ-calculus formula to describe the controllability constraint(that uncontrollable events of plants are never disabled by a supervisor), we absorb this constraint as part of quotienting which allows us to directly capture more general state-dependent controllability constraints. Finally, we develop a tableau-based technique for verifying satisfiability of quotiented formula and model generation. The runtime for the technique is exponential in terms of the size of the plan and the control specification. A better complexity result that is polynomial to plant size and exponential to specification size is obtained when the controllability property is state-independent. A prototype implementation in a tabled logic programming language as well as some experimental results are presented.

Deadlock-free dynamic resource assignment in multi-robot systems with multiple missions:application in wireless sensor networks

In unstructured environments, dynamic resource assignment is required for effective cooperation of robot teams. In some scenarios, robots are in charge of executing multiple missions simultaneously. This creates risks of deadlock due to the presence of shared resources among various missions. The main contribution of this paper is the development of a novel approach that combines the one-step look-ahead deadlock avoidance policy with dynamic resource assignment. The dynamicresource assignment is achieved using greedy resource assignment for multi-mission robot teams in the framework of a matrix-based discrete event controller. Simulation results are presented in MATLAB to discuss in detail the proposed control strategy. The paper also discusses the toolkit developed in LabVIEW which is used to implement this control framework using a suitable example.

Application of networked discrete event system theory on intelligent transportation systems

The responses of vehicles to the changes in traffic situations inevitably have delays in observing an event and implementing a control command,which often causes fatal accidents.So far,the methods for handling delays are empirical and cannot be mathematically proven.To eliminate the accidents caused by such delays,in this paper,we develop mathematically provable methods to handle these delays.Specifically,we use networked discrete event systems to model the process of driving vehicles and present a supervisory controller for handling delay situations.The method developed in this paper could serve as a new start for modeling and controlling the responsive behaviors of self-driving vehicles in the future.

An Improved Approach to Test Diagnosability of Bounded Petri Nets

For bounded Petri nets, Cabasino et al. propose a diagnosability test method that is based on the analysis of a modified basis reachability graph and a basis reachability diagnoser. However, its complexity is exponential in the number of nodes of the basis reachability diagnoser. In order to reduce the complexity of their method, this paper presents a new diagnosability test approach for bounded Petri nets. We present the concept of an extended basis reachability graph and prove that our approach is of polynomial complexity in the number of nodes of extended basis reachability graphs. An example is given to illustrate the application of the presented approach.

Resilient Fault Diagnosis Under Imperfect Observations–A Need for Industry 4.0 Era

In smart industrial systems,in many cases,a fault can be captured as an event to represent the distinct nature of subsequent changes.Event-based fault diagnosis techniques are capable model-based methods for diagnosing faults from a sequence of observable events executed by the system under diagnosis.Most event-based diagnosis techniques rely on perfect observations of observable events.However,in practice,it is common to miss an observable event due to a problem in sensorreadings or communication/transmission channels.This paper develops a fault diagnosis tool,referred to as diagnoser,which can robustly detect,locate,and isolate occurred faults.The developed diagnoser is resilient against missed observations.A missed observation is detected from its successive sequence of events.Upon detecting a missed observation,the developed diagnoser automatically resets and then,asynchronously resumes the diagnosis process.This is achieved solely based on postreset/activation observations and without interrupting the performance of the system under diagnosis.New concepts of asynchronous detectability and asynchronous diagnosability are introduced.It is shown that if asynchronous detectability and asynchronous diagnosability hold,the proposed diagnoser is capable of diagnosing occurred faults under imperfect observations.The proposed technique is applied to diagnose faults in a manufacturing process.Illustrative examples are provided to explain the details of the proposed algorithm.The result paves the way towards fostering resilient cyber-physical systems in Industry4.0 context.

Post-Processing Time-Aware Optimal Scheduling of Single Robotic Cluster Tools

Integrated circuit chips are produced on silicon wafers.Robotic cluster tools are widely used since they provide a reconfigurable and efficient environment for most wafer fabrication processes.Recent advances in new semiconductor materials bring about new functionality for integrated circuits.After a wafer is processed in a processing chamber,the wafer should be removed from there as fast as possible to guarantee its high-quality integrated circuits.Meanwhile,maximization of the throughput of robotic cluster tools is desired.This work aims to perform post-processing time-aware scheduling for such tools subject to wafer residencytime constraints.To do so,closed-form expression algorithms are derived to compute robot waiting time accurately upon the analysis of particular events of robot waiting for singlearm cluster tools.Examples are given to show the application and effectiveness of the proposed algorithms.

Modeling and Stability Analysis of a Communication Network System

In this work, the modeling and stability problem for a communication network system is addressed. The communication network system consists of a transmitter which sends messages to a receiver. The proposed model considers two possibilities. The first one, that messages are successfully received, while in the second one, during the sending process the transmitter breaks down and as a result the message does not reach the receiver. Timed Petrinets is the mathematical and graphical modeling technique utilized. Lyapunov stability theory provides the required tools needed to aboard the stability problem. Employing Lyapunov methods, a sufficient condition for stabilization is obtained. It is shown that it is possible to restrict the communication network system state space in such a way that boundedness is guaranteed. However, this restriction results to be vague. This inconvenience is overcome by considering a specific recurrence equation, in the max-plus algebra, which is assigned to the timed Petri net graphical model.

Modular supervisory control for multi-floor manufacturing processes

Due to space availability limitations and high land costs,there is an increasing development of multi-floor manufacturing(MFM)systems in urban and industrial areas.The problem of coordination in a multi-floor manufacturing process,in the Ramadge Wonham framework,is introduced.The manufacturing chain of each floor and the elevator system are modeled in the form of finite deterministic automata.The models of the multi-floor manufacturing process are parametric with respect to the number of floors and the number of manufacturing machines on each floor.The coordination desired performance is formulated in the form of desired regular languages in analytic forms.The languages are realized by appropriate supervisors in the form of finite deterministic automata.The models of the supervisors are also parametric with respect to the number of floors and the number of manufacturing machines on each floor.The total control of the coordination of the multi-floor manufacturing process is accomplished via a modular supervisory control architecture.The complexity of the supervisors as well as the complexity of the total modular supervisory architecture are determined in analytic forms with respect to the number of floors and the number of manufacturing machines on each floor.The special case of a two floor manufacturing process is presented as an illustrative example.

Application of dynamic sensor activation on operating automated headlights

The controller in an automated vehicle relies on sensors to collect the information needed for handling traffic situations,and reducing the frequency of using sensors could prolong theirlifespans.We present in this paper the application of dynamic sensor activation algorithms in discrete event systems to activate/deactivate sensors for colecting information when it is only necessary to automatically operate headlights based on trafic rules.The framework developed in this paper forms a basis for automatically activating/deactivating sensors for other components in an automated vehicle in the future.

Compatible-invariant subset analysis of deterministic finite automata via semi-tensor product of matrices approach

The compatible-invariant subset of deterministic finite automata（ DFA） is investigated to solve the problem of subset stabilization under the frameworks of semi-tensor product（ STP） of matrices. The concepts of compatibleinvariant subset and largest compatible-invariant subset are introduced inductively for Moore-type DFA,and a necessary condition for the existence of largest compatible-invariant subset is given. Meanwhile,by using the STP of matrices,a compatible feasible event matrix is defined with respect to the largest compatible-invariant subset.Based on the concept of compatible feasible event matrix,an algorithm to calculate the largest compatible-invariant subset contained in a given subset is proposed. Finally,an illustrative example is given to validate the results.

Complexity of comparing expressions in max-plus algebra

Max-plus algebra has been widely used in the study of discrete-event dynamic systems.Using max-plus algebra makes it easy to specify safety constraints on events since they can be described as a set of inequalities of state variables,i.e.,firing times of relevant events.This paper proves that the problem of solving max-plus inequalities in a cube(MAXINEQ)is nondeterministic polynomial-time hard(NP-hard)in strong sense and the problem of verifying max-plus inequalities(VERMAXINEQ)is co-NP.As a corollary,the problem of solving a system of multivariate max-algebraic polynomial equalities and inequalities(MPEI)is shown to be NP-hard in strong sense.The results indicate the difficulties in comparing max-plus formulas in general.Problem structures of specific systems have to be explored to enable the development of efficient algorithms.