Petri-net-based supervisory control of discrete event systems and their ladder logic diagram implementations

The last decade has witnessed rapid developments in computer technology, which inreturn, has found widespread applications in manufacturing systems, communicationnetworks, robots etc. Such systems are called Discrete Event Systems (DESs), in whichproperties such as non-determinism, conflict and parallelism are exhibited. As DESsbecome more complex, the need for an effective design tool and its implementationbecomes more important. Supervisory control theory, based on finite state machines(FSM) and formal languages, is a well established framework for the study of DESs. Insupervisory control, given a model of the system and the desired system behaviourspecifications, the objective is to find a supervisor (controller) such that the controlledbehaviour of the system does not contradict the specifications given and does notunnecessarily constrain the behaviour of the system. In general, the classes ofspecifications that have been considered within the supervisory control fall into twocategories: the forbidden state problem, in which the control specifications are expressedas forbidden conditions that must be avoided, and the desired string problem, in whichthe control specifications are expressed as sequence of activities that must be provided.In supervisory control, there are some problems when using FSMs as an underlyingmodelling tool. Firstly, the number of states grows exponentially as the system becomesbigger. Secondly, FMSs lack from graphical visivalisation. To overcome these problemsPetri nets have been considered as an alternative modelling tool for the analysis, designand implementation of such DESs, because of their easily understood graphicalrepresentation in addition to their well formed mathematical formalism.The thesis investigates the use of Petri nets in supervisory control. Both the forbiddenstate problem and the desired string problem are solved. In other words, this workpresents systematic approaches to the synthesis of Petri-nets-based supervisors(controllers) for both the forbidden state problem and the desired string problem andintroduces the details of supervisory design procedures. The supervisors obtained are the form of a net structure as oppose to supervisors given as a feedback fiinction. Thismeans that a controlled model of the system can be constructed and analysed using thetechniques regarding to Petri net models.In particular the thesis considers discrete manufacturing systems. The results obtainedcan be applied to high level control of manufacturing systems, where the role of thesupervisor is to coordinate the control of machines, robots, etc. and to low-level controlof manufacturing systems, where the role of the supervisor is to arrange low-levelinteractions between the control devices, such as motors, actuators, etc.An approach to the conversion from the supervisors to ladder logic diagrams (LLDs)for implementation on a programmable logic controller (PLC) is proposed. A discretemanufacturing system example is then considered. The aim of this is to illustrate theapplicability, strengths and drawbacks of the design techniques proposed

An improved artificial dendrite cell algorithm for abnormal signal detection

In dendrite cell algorithm (DCA), the abnormality of a data point is determined by comparing the multi-context antigen value (MCAV) with anomaly threshold. The limitation of the existing threshold is that the value needs to be determined before mining based on previous information and the existing MCAV is inefficient when exposed to extreme values. This causes the DCA fails to detect new data points if the pattern has distinct behavior from previous information and affects detection accuracy. This paper proposed an improved anomaly threshold solution for DCA using the statistical cumulative sum (CUSUM) with the aim to improve its detection capability. In the proposed approach, the MCAV were normalized with upper CUSUM and the new anomaly threshold was calculated during run time by considering the acceptance value and min MCAV. From the experiments towards 12 benchmark and two outbreak datasets, the improved DCA is proven to have a better detection result than its previous version in terms of sensitivity, specificity, false detection rate and accuracy

Process Mining of Programmable Logic Controllers: Input/Output Event Logs

This paper presents an approach to model an unknown Ladder Logic based Programmable Logic Controller (PLC) program consisting of Boolean logic and counters using Process Mining techniques. First, we tap the inputs and outputs of a PLC to create a data flow log. Second, we propose a method to translate the obtained data flow log to an event log suitable for Process Mining. In a third step, we propose a hybrid Petri net (PN) and neural network approach to approximate the logic of the actual underlying PLC program. We demonstrate the applicability of our proposed approach on a case study with three simulated scenarios

Supervisor Localization of Discrete-Event Systems based on State Tree Structures

Recently we developed supervisor localization, a top-down approach to distributed control of discrete-event systems in the Ramadge-Wonham supervisory control framework. Its essence is the decomposition of monolithic (global) control action into local control strategies for the individual agents. In this paper, we establish a counterpart supervisor localization theory in the framework of State Tree Structures, known to be efficient for control design of very large systems. In the new framework, we introduce the new concepts of local state tracker, local control function, and state-based local-global control equivalence. As before, we prove that the collective localized control behavior is identical to the monolithic optimal (i.e. maximally permissive) and nonblocking controlled behavior. In addition, we propose a new and more efficient localization algorithm which exploits BDD computation. Finally we demonstrate our localization approach on a model for a complex semiconductor manufacturing system

Mixed-integer-linear-programming-based energy management system for hybrid PV-wind-battery microgrids: Modeling, design, and experimental verification

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksMicrogrids are energy systems that aggregate distributed energy resources, loads, and power electronics devices in a stable and balanced way. They rely on energy management systems to schedule optimally the distributed energy resources. Conventionally, many scheduling problems have been solved by using complex algorithms that, even so, do not consider the operation of the distributed energy resources. This paper presents the modeling and design of a modular energy management system and its integration to a grid-connected battery-based microgrid. The scheduling model is a power generation-side strategy, defined as a general mixed-integer linear programming by taking into account two stages for proper charging of the storage units. This model is considered as a deterministic problem that aims to minimize operating costs and promote self-consumption based on 24-hour ahead forecast data. The operation of the microgrid is complemented with a supervisory control stage that compensates any mismatch between the offline scheduling process and the real time microgrid operation. The proposal has been tested experimentally in a hybrid microgrid at the Microgrid Research Laboratory, Aalborg University.Peer ReviewedPostprint (author's final draft