A language measure for partially observed discrete event supervisory control systems

We develop a process-theoretic approach for generally-dis-tributed discrete-event systems with unrestricted nondeterminism that is geared towards supervisory control. Supervisory control theory deals with synthesis of models of supervisory controllers that ensure safe and nonblocking behavior of the supervised system. The models are synthesized based on a model of the uncontrolled system and a formalization of the control requirements. Even though there exist extensions of supervisory control theory for timed and Markovian discrete-event systems, there are hardly any investigations of supervisory control of discrete-event systems with generally-distributed delays. General distributions provide for (convenient) modeling of important real-world phenomena that cannot be consistently modeled by means of real time or Markovian (exponentially-distributed) delays, like heavy-tail or uniformly distributed processes. Our theory relies on a behavioral preorder termed partial bisimulation, for which we provide a suitable extension. Based on the proposed theory we provide for an appropriate abstraction of the stochastic behavior, which enables us to employ standard supervisory controller synthesis tools. The synthesized supervisor can, thereafter, be coupled with the stochastic model of the unsupervised system and abstracted to a generalized semi-Markov process for the purpose of analysis and simulation.

Distributed supervisory control is a method to synthesize local controllers in discrete-eventsystems with a systematic observation of the plant. Some works were reported on extending this methodby which local controllers are constructed so that observation properties are preserved from monolithic todistributed supervisory control, in an up-down approach. In this paper, we find circumstances in whichobservation properties are preserved from monolithic to distributed supervisory control. Local observationproperties, i.e. local normality and local relative observability are employed for investigating observationproperties of each local controller, which are constructed by any localization algorithm that preserves controlequivalency to the monolithic supervisor with respect to the plant. These properties enable us to investigatethe observation properties from monolithic to distributed supervisory control. Moreover, observationequivalence property is defined according to the control equivalence in a distributed supervisory controlwith partial observation. It is proved that with preserving observation equivalence of the local controllers tothe monolithic supervisor, the control equivalence is satisfied, if and only if the intersection of local eventsets is a subset of or equal to the global observable event set.

Robust nonblocking supervisory control of discrete-event systems under partial observation

The economic aspects of the online, programmable computer for supervisory control of producing operations are discussed. The material presented reflects the performance and economics of a pilot supervisory control installation that has been supervising and controlling producing operations for one year in two widely separated fields in southeastern New Mexico. Expansion of this pilot supervisory system is necessary to obtain an actual payout, but the performance of the pilot project does provide a reliable basis for predicting the economics of full scale computer controlled producing operations. Introduction A pilot installation to evaluate a supervisory, monitoring and control system for properties operated in southeastern New Mexico by Continental Oil Co. was installed in Oct., 1964. The pilot project included 56 wells in two fields to be controlled from the district office in Hobbs, N. M. Results of the pilot project would serve to evaluate the economics of expanding the system to include three additional areas and 326 additional wells in a full scale operation, with possible future expansion to a total of 600 to 700 wells. The pilot installation and three additional areas to be included in the full scale project are shown in Fig. 1.This supervisory control system is similar in concept to an earlier system installed during 1962 in the Big Horn Basin of Wyoming by the Rocky Mountain Region of Conoco. The pilot project has been sufficiently complex to prove equipment capability and performance, but limited enough to keep installation costs within reason should results indicate the total project to be economically unattractive leases in the Hobbs and El Mar fields of New Mexico comprise this two-field pilot project. These areas are separated by approximately 56 air miles (Fig. 1). The Hobbs field, located two miles from the central supervisory in the city of Hobbs, consists of three leases with 14 flowing or pumping wells producing 5 1 8 BOPD into one central tank battery. The El Mar field includes three leases with 42 pumping or flowing wells producing 700 BOPD into a central tank battery. The objective of the pilot program was to determine if a significant portion of the pumper functions could be performed by the supervisory system while maintaining producing efficiency at a level equal to or greater than before. It was recognized that not all of the pumper duties could be performed by computer control but that almost all of the check-and-see type routine could be surveyed by the system. The majority of pumper time involves travel and inspection duties; therefore, it was estimated that approximately 50 per cent of his assignments could be supervised by the control system. JPT P. 48ˆ

Recently we proposed relative observability for supervisory control of discrete-event systems under partial observation. Relative observability is closed under set unions and hence there exists the supremal relatively observable sublanguage of a given language. In this paper we present a new characterization of relative observability, based on which we design an algorithm that computes the supremal sublanguage. This algorithm is formulated in terms of languages, thereby separating out the linguistic essence of the problem from the implementational aspects of state computation using automaton models. Exploiting the linguistic concept of support based on Nerode equivalence, we prove that for regular languages the algorithm is finitely convergent to the supremal sublanguage.

We identify a new observability concept, called relative observability, in supervisory control of discrete-event systems under partial observation. A fixed, ambient language is given, relative to which observability is tested. Relative observability is stronger than observability, but enjoys the important property that it is preserved under set union; hence there exists the supremal relatively observable sublanguage of a given language. Relative observability is weaker than normality, and thus yields, when combined with controllability, a generally larger controlled behavior; in particular, no constraint is imposed that only observable controllable events may be disabled. We design new algorithms which compute the supremal relatively observable (and controllable) sublanguage of a given language, which is generally larger than the normal counterpart. We demonstrate the new observability concept and algorithms with a Guideway and an AGV example.

The paper proposes the design of the supervisory heuristic fuzzy control system applied to a Sequencing Batch Reactor (SBR) in the Wastewater Treatment Plant (WWTP). Based on real data records and the biological process and aeration system models, a control system for biological processes has been designed. The supervisory control system performs management of the reactor work cycle, determines the phase length, controls the sludge age, calculates the setpoint of dissolved oxygen, and adapts parameters of the lower control layer. The results of simulation tests for the case study wastewater treatment plant are presented.

A hybrid supervisory control system using a recurrent fuzzy neural network (RFNN) is proposed to control the mover of a permanent magnet linear synchronous motor (PMLSM) servo drive for the tracking of periodic reference inputs. First, the field-oriented mechanism is applied to formulate the dynamic equation of the PMLSM. Then, a hybrid supervisory control system, which combines a supervisory control system and an intelligent control system, is proposed to control the mover of the PMLSM for periodic motion. The supervisory control law is designed based on the uncertainty bounds of the controlled system to stabilize the system states around a predefined bound region. Since the supervisory control law will induce excessive and chattering control effort, the intelligent control system is introduced to smooth and reduce the control effort when the system states are inside the predefined bound region. In the intelligent control system, the RFNN control is the main tracking controller which is used to mimic a idea control law and a compensated control is proposed to compensate the difference between the idea control law and the RFNN control. The RFNN has the merits of fuzzy inference, dynamic mapping and fast convergence speed, In addition, an online parameter training methodology, which is derived using the Lyapunov stability theorem and the gradient descent method, is proposed to increase the learning capability of the RFNN. The proposed hybrid supervisory control system using RFNN can track various periodic reference inputs effectively with robust control performance.

Human performance in problem solving in the context of supervisory control of discrete-event systems is discussed. Software packages for such problems usually offer only rudimentary support in the form of visual data entry and algorithmic computations. Other activities such as system modeling and verification of the solution have to be done without computer support. This work is a first step in understanding how humans approach discrete-event control problems. An observational study is described, where subjects are video-taped solving supervisory control problems. One video recording is used to construct a taxonomy of the task and then the different activities of the subject are encoded accordingly. The data are analysed to discover patterns of human activity. These results can be used to guide the design of software for computer-aided problem solving in this context.

In the context of supervisory control of discrete-event systems, decentralized control is a well-established area of research. In this paper we present an implementation of such controllers for an assembly cell with two-assembly stations (SCARA robots), in a laboratory scale computer integrated manufacturing (CIM) system. Step by step implementation, conflict avoidance between local supervisors and difficulties encountered are discussed. Petri nets are used as the modelling tool and Lin and Wonham framework is used as the control architecture. Assembly stations are modelled as intelligent agents. A separate software module called order processing module (OPM) is used to handle orders into and out of the system and to schedule the two-assembly stations

We consider a multi-adversary version of the supervisory control problem for discrete-event systems (DES), in which an adversary corrupts the observations available to the supervisor. The supervisor’s goal is to enforce a specific language in spite of the opponent’s actions and without knowing which adversary it is playing against. This problem is motivated by applications to computer security in which a cyber defense system must make decisions based on reports from sensors that may have been tampered with by an attacker. We start by showing that the problem has a solution if and only if the desired language is controllable (in the DES classical sense) and observable in a (novel) sense that takes the adversaries into account. For the particular case of attacks that insert symbols into or remove symbols from the sequence of sensor outputs, we show that testing the existence of a supervisor and building the supervisor can be done using tools developed for the classical DES supervisory control problem, by considering a family of automata with modified output maps, but without expanding the size of the state space and without incurring on exponential complexity on the number of attacks considered.

The aim of this essay is to provide a brief introduction to supervisory control theory of discrete-event systems.

This paper proposes a solution to the electric Vehicle Scheduling Problem (eVSP) based on the framework of Discrete Event System (DES). A supervisory control is synthesized using the theory of Supervisory Control of Discrete Event System (SCDES) to manage the power admission control of a group of local Plug-in Electric Vehicles (PEV). The PEVs are categorized based on their level of priority to be charged and an algorithm is developed to allocate power to PEVs according to their priority and available capacity. The proposed algorithm and supervisor validates the schedulability of charging of PEVs while meeting the constraint of the grid to achieve peak demand reduction. Simulation studies are carried out using MATLAB/Simulink and STATEFLOW toolkit and the result validates the effectiveness of the control scheme to reduce peak demand while providing fair charging schedules to PEVs.

This paper modifies the signed real measure of regular languages, which has been reported in recent literature for analysis and synthesis of discrete event supervisory control laws. A new concept of renormalized measure is introduced to eliminate a user-selectable parameter in the present version of the language measure. The concept of measure renormalization is illustrated by an example.

Supervisory control of discrete-event systems: A brief history