Showing papers on "Supervisory control published in 2022"
TL;DR: In this paper , the authors extended vector-SNP to explore the system's intrinsic stability properties without configuration attention by introducing two classes of structural feature vectors: N-invariants and R-invaris, and a typical style of specifications, namely neuron mutual exclusion inequality constraints, is advanced for supervisory control using SNPs.
13 citations
TL;DR: In this article , the authors investigated the adaptability of Q-learning based supervisory control for hybrid electric vehicle (HEV) energy management for its adaptability in real-world driving scenarios, conditions such as vehicle loads, road conditions and traffic conditions.
Abstract: As one of adaptive optimal controls, the Q-learning based supervisory control for hybrid electric vehicle (HEV) energy management is rarely studied for its adaptability. In real-world driving scenarios, conditions such as vehicle loads, road conditions and traffic conditions may vary. If these changes occur and the vehicle supervisory control does not adapt to it, the resulting fuel economy may not be optimal. To our best knowledge, for the first time, the study investigates the adaptability of Q-learning based supervisory control for HEVs. A comprehensive analysis is presented for the adaptability interpretation with three varying factors: driving cycle, vehicle load condition, and road grade. A parallel HEV architecture is considered and Q-learning is used as the reinforcement learning algorithm to control the torque split between the engine and the electric motor. Model Predictive Control, Equivalent consumption minimization strategy and thermostatic control strategy are implemented for comparison. The Q-learning based supervisory control shows strong adaptability under different conditions, and it leads the fuel economy among four supervisory controls in all three varying conditions.
13 citations
TL;DR: In this article , the authors developed online risk models that can be updated as conditions change, using risk as one metric to control an autonomous ship in operation, which enables the control system to make better and more informed decisions than existing ship control systems.
9 citations
TL;DR: In this paper , the authors consider the supervisory control layer of CPSs, focusing on closed-loop control systems vulnerable to sensor-reading modification attacks (SM-attacks), which may disguise the occurrence of an event as a different event by modifying appropriately sensor readings in sensor communication channels.
Abstract: In cyber–physical systems (CPSs), it is of great importance to handle network attack issues. In this article, we consider the supervisory control layer of CPSs, focusing on closed-loop control systems vulnerable to sensor-reading modification attacks (SM-attacks), which may disguise the occurrence of an event as a different event by modifying appropriately sensor readings in sensor communication channels. In particular, we consider the plant modeled as a bounded Petri net and the control specification consisting in liveness enforcing. Based on repeatedly computing a more restrictive liveness-enforcing supervisor under no attack and constructing a so-called basic supervisor, a method that synthesizes a liveness-enforcing supervisor tolerant to an SM-attack is proposed.
9 citations
TL;DR: This work has proposed, a novel deliberative/reactive hybrid architecture based on the supervisory control theory (SCT), which has incorporated safety requirements as well as heuristics’ performance requirements into the system.
Abstract: In a multi-robot system, several robots coordinate to perform a joint task such as border patrol, etc. There are many different methods which can be employed to model a multi-robot system. Some of these techniques are based on the discrete events systems theory. In this work, we have proposed, a novel deliberative/reactive hybrid architecture based on the supervisory control theory (SCT). We have incorporated safety requirements as well as heuristics’ performance requirements into our system. We have validated our proposed architecture via several computer simulations. Simulation results confirm the effectiveness of the proposed architecture.
8 citations
TL;DR: In this paper , a distributed supervisory control scheme, considering the possibility of system faults, was designed to preserve the efficient functionality of a pressurized reactor unit in the presence of faults.
Abstract: The preservation of the efficient functionality of a pressurized reactor unit in the presence of faults is the aim of the present paper. To satisfy this aim, a distributed supervisory control scheme, considering the possibility of system faults, was designed. Towards this aim, the models of the subsystems of the total pressurized reactor unit in the presence of sensor and actuator faults are developed, using finite deterministic automata. This is the first contribution of the paper. The desired performance of the unit was formulated in the form of rules guaranteeing the desired behavior of a pressurize–depressurize cycle and safety specifications. The rules were translated to six desired regular languages. The realization of these languages, in the form of supervisor automata, was accomplished. This is the second contribution of the paper. A modular supervisory design scheme, towards safety and tolerance in the presence of faults, was proposed and realized, and the properties of the proposed supervisors and the controlled automaton were proven. This is the third contribution of the paper. The complexity of each supervisor was computed. The efficiency of the supervisory design scheme was illustrated through simulations. A PLC implementation of the derived supervisors was proposed. The derived supervisors are suitable for implementation as function blocks.
8 citations
TL;DR: In this article , the robust control problem of discrete event systems assuming that replacement attacks may occur, thus making it appear that an event that has occurred looks like another event, is addressed.
Abstract: This article addresses the robust control problem of discrete event systems assuming that replacement attacks may occur, thus making it appear that an event that has occurred looks like another event. In particular, we assume that this is done by tampering with the sensor-readings in the sensor communication channel. Specifically, we use Petri nets as the reference formalism to model the plant and assume a control specification in terms of a generalized mutual exclusion constraint. We propose three different methods to derive a control policy that is robust to the possible replacement attacks. The first two methods lead to an optimal (i.e., maximally permissive) policy but are computationally inefficient when applied to large-size systems. On the contrary, the third method computes a policy more efficiently and reveals more easily implementable in practice. However, this is done at the expense of optimality.
8 citations
17 Jun 2022
TL;DR: In this article , a flexible and extensible architecture to integrate WSN and IoT is presented, where REST based internet services as used as a layer interoperating as an application layer which has a possibility of being integrated directly into the other domains of application to remotely monitor smart homes, VAN (Vehicular area networks) or healthcare services.
Abstract: There is an increased use of WSN (Wireless Sensor Networks) in our daily lives with WSN finding application in different areas like maintaining health, better quality of life scenarios, production monitoring in industries, traffic control and various other fields. WSNs have a scope for being incorporated in IoT (Internet of Things). IoT is beneficial foe Web based applications having specific requirements of storage and computation. This paper gives a flexible and extensible architecture to integrate WSN and IoT. REST based internet services as used as a layer interoperating as an application layer which has a possibility of being integrated directly into the other domains of application to remotely monitor smart homes, VAN (Vehicular area networks) or healthcare services.
7 citations
TL;DR: In this paper, a safety distance-based hierarchical AEB control system constituted of a high-level Rule-Based Supervisory control module, an intermediate-level switching algorithm and a low-level control module was proposed.
6 citations
TL;DR: In this article , the authors introduce model deltas as a means to describe the difference between pairs of models, and introduce a notion of atomic adaptations to compute the supervisor for the adapted model in a transformational manner.
Abstract: Abstract Supervisory controller synthesis is a means to compute correct-by-construction controllers for discrete event systems. As these systems and their requirements evolve over time, an updated supervisor needs to be computed each time an adaptation takes place. We consider the case that a supervisor has been synthesized for a given model, after which this model is (slightly) adapted. We investigate how we can make use of the previous synthesis result, in order to more efficiently compute the supervisor for the adapted model. We introduce model deltas as a means to describe the difference between pairs of models. Using the model deltas, a notion of atomic adaptations is introduced. For these atomic adaptations, algorithms are provided to compute the supervisor for the adapted model in a transformational manner from the previous synthesis result, rather than performing a completely new synthesis. These atomic adaptations can be iterated over, to transformationally compute a supervisor for model deltas that contain a number of atomic adaptations. To improve efficiency, it is shown how atomic adaptations can be grouped together based on their required computations and be processed at the same time. A running example is used to support the explanations on the functioning of the algorithms. The efficiency of the method is evaluated by means of both an academic and an industrial use case.
6 citations
TL;DR: In this article , a supervisory controller (SC) is designed based on the supervisory control theory (SCT) of discrete event systems to transfer from the grid-connected mode and operate a battery-enhanced electric vehicles' dc fast charging (DCFC) station in the autonomous mode, when the supply grid is not available.
Abstract: This article develops, evaluates, and verifies a supervisory controller (SC) to transfer from the grid-connected mode and operate a battery-enhanced electric vehicles’ (EVs) dc fast charging (DCFC) station in the autonomous mode, when the supply grid is not available. The SC is designed based on the supervisory control theory (SCT) of discrete event systems and is based on a rigorous mathematical process; nonblocking, i.e., avoids entering an operational deadlock scenario that leads to the system collapse; minimally restrictive with respect to the station's discrete behavior; modular; and scalable. The SC also operates the station in the grid-connected mode and provides a seamless transition between the two modes and thus the DCFC station is also synonymous with a dc-microgrid. The SC is implemented on an industrial programmable logic controller and its performance is verified in a real-time hardware-in-the-loop environment using an OPAL-RT testbed.
TL;DR: In this paper , a new supervisory control approach is presented based on MPC method, using a stochastic optimization model, and the objective function of the proposed central controller consists of the combined cost-based and system-based parts.
TL;DR: In this paper , the authors investigate quantitative supervisory control with local mean payoff objectives on discrete event systems modeled as weighted automata, where weight flows are generated as new events occur, which are required to satisfy some quantitative conditions.
Abstract: This article investigates quantitative supervisory control with local mean payoff objectives on discrete event systems modeled as weighted automata. Weight flows are generated as new events occur, which are required to satisfy some quantitative conditions. We focus on mean weights (payoffs) over a finite number of events, which serve as a measure for the stability or robustness of weight flows. The range of events to evaluate the mean payoff is termed a window, which slides as new events occur. Qualitative requirements such as safety and liveness are also necessary along with quantitative requirements. Supervisory control is employed to manipulate the operation of the system so that the requirements are satisfied. We consider two different scenarios based on whether the window size is fixed or not. Correspondingly, we formulate two supervisory control problems, both of which are solved sequentially by first tackling the qualitative issues and then the quantitative ones. The automaton model is then transformed to a two-player game between the supervisor and the environment, where safety and liveness are enforced. Based on the intermediate results, several quantitative objectives are defined to formulate two games, which correspond to the two proposed supervisory control problems. Finally, we synthesize provably correct supervisors by solving the games and completely resolve both problems.
TL;DR: In this article , a new approach for online estimation and control of networked discrete-event systems (DESs) with control delays is proposed, where supervisors send control decisions to plants via communication channels subject to communication delays.
Abstract: We investigate state estimation and safe controller synthesis for networked discrete-event systems (DESs), where supervisors send control decisions to plants via communication channels subject to communication delays. Previous works on state estimation of networked DES are based on the open-loop system without utilizing the knowledge of the control policy. In this article, we propose a new approach for online estimation and control of networked DES with control delays. We first propose a new state estimation algorithm for the closed-loop system utilizing the information of control decision history. The proposed state estimation algorithm can be implemented recursively upon the occurrence of each new observable event. Then we investigate how to predict the effect of control delays in order to calculate a control decision online at each instant. We show that the proposed online supervisor can be updated effectively and the resulting closed-loop behavior is safe. Furthermore, we compare the proposed online supervisor with the predictive supervisor proposed in the literature and show that our proposed online supervisor is more permissive than predictive supervisor in the sense of language inclusion.
TL;DR: A robust CPM model for varying-dimensional time-series data resulting from the missing variables in SCADA systems is developed by developing parameters-shared node-effect and edge-effect graph neural networks (GNNs).
Abstract: The supervisory control and data acquisition (SCADA) system provides information that can be used to free humans from laborious monitoring tasks, such as control performance monitoring (CPM). However, the existing CPM methods rely heavily on the quality of SCADA data. In practice, the missing of measurement and computed signals due to some random and man-induced factors will lead to failures of traditional CPM methods. This article develops a robust CPM model for varying-dimensional time-series data resulting from the missing variables in SCADA systems. Two attractive advantages of the proposed model are noticed. First, SCADA data with various variable dimensions and missing patterns can be handled through a structural feature extraction (SFE) module, which constructs specific graphs for input data and explicitly explores the inherent interaction mechanism among variables. A structural vector is then generated to characterize the interaction pattern of multiple variables. Second, the proposed model is designed with the generalization ability by developing parameters-shared node-effect and edge-effect graph neural networks (GNNs). In this way, the method shows good robustness to the previously unseen missing patterns. Experiments on the simulated and real datasets demonstrate the feasibility of this method.
14 Jan 2022
TL;DR: In this paper , the authors studied the security problem of protecting secrets in discrete-event systems modeled by deterministic finite automata and showed that the problem is transformed to a supervisory control problem in the security automaton.
Abstract: In this paper we study a security problem of protecting secrets in discrete-event systems modeled by deterministic finite automata. In the system some states are defined as secrets, each of which is associated with a security level. The problem is to design an event-protecting policy such that any event sequence from the initial state that reaches a secret state contains a number of protected events no less than the required level of security. To solve this secret securing problem, we first develop a layered structure called the security automaton. Then we show that the problem is transformed to a supervisory control problem in the security automaton. We consider two criteria of optimality on protecting policies: (1) disruptiveness, i.e., protecting policies with a minimum degree of disturbance to legal users' normal operations; (2) cost, i.e., protecting policies with a minimal cost. For the optimality on disruptiveness, we prove that a minimally disruptive protecting policy is obtained by using the classical supervisory control theory in the security automaton. For the optimality on cost, we develop a method to obtain a protecting policy with minimal cost by finding a min-cut in the security automaton.
TL;DR: In this paper , a novel framework for the supervisory control of timed discrete event systems based on Time Petri nets is introduced, which relies on the construction of a partial forward reachability graph of the modified state class graph type and the formulation of integer linear programming problems to establish suitable firing time intervals (FTIs) for the controllable transitions.
Abstract: A novel framework is introduced for the supervisory control (SC) of timed discrete event systems based on Time Petri nets. The method encompasses both logical (markings to reach or avoid) and temporal specifications (arrival and departure times in specific markings). It relies on the construction of a partial forward reachability graph of the modified state class graph type and the formulation of integer linear programming problems to establish suitable firing time intervals (FTIs) for the controllable transitions. For each enabled controllable transition, the SC algorithm provides the largest FTI that that the specifications are met, irrespectively of the firing times of the uncontrollable transitions.
TL;DR: In this paper , the authors present the design and construction of a vacuum control system for the Space Plasma Environment Research Facility (SPERF) to set up an appropriate vacuum environment for plasma experiments, including the terrestrial space and near space vacuum control systems.
Abstract: The Space Plasma Environment Research Facility (SPERF) is a ground simulation user facility for studying the space plasma physical processes. This study presents the design and construction of a vacuum control system for the SPERF to set up an appropriate vacuum environment for plasma experiments, including the terrestrial space and near space vacuum control systems. Based on the requirements of remote automation, distributed control, centralized management, high reliability, expansibility, and safety, the architecture of the vacuum control system has been divided into three levels. Among these, the local level is the most essential part of the control system, which adopts the programmable logical controller (PLC) with Siemens S7-1500 CPU as the core. The PLC supports multiple communication protocols and can accurately control and monitor the actuators in the process of establishing a vacuum environment. Furthermore, it has the ability to communicate and interact with remote upper computers and the central control system through the supervisory control and data acquisition (scada) software developed based on iFix. Based on the architecture of the vacuum control system, the control process for establishing the vacuum environment, including the ultimate vacuum and experimental vacuum, was designed. It is noteworthy that in experimental vacuum acquisition, the injection of working fluid gas is controlled directly by the central control system, considering the different requirements of the terrestrial space and near space systems for the experimental working pressure and flexibility of the experimental vacuum control. The vacuum control system designed in this study provides technical support for the SPERF to perform the plasma experiments successfully. In addition, it offers reference and insights for the design of vacuum control systems in similar large-scale plasma simulation facilities.
TL;DR: In this paper , an on-the-fly Partial-Order Reduction (POR) technique is proposed to preserve both functional and performance properties in the synthesized supervisory controller, which improves the scalability of the synthesis and any subsequent performance analysis.
Abstract: A key challenge in the synthesis and subsequent analysis of supervisory controllers is the impact of state-space explosion caused by concurrency. The main bottleneck is often the memory needed to store the composition of plant and requirement automata and the resulting supervisor. Partial-order reduction (POR) is a well-established technique that alleviates this issue in the field of model checking. It does so by exploiting redundancy in the model with respect to the properties of interest. For controller synthesis, the functional properties of interest are nonblockingness, controllability, and least-restrictiveness, but also performance properties, such as throughput and latency are of interest. We propose an on-the-fly POR on the input model that preserves both functional and performance properties in the synthesized supervisory controller. This improves the scalability of the synthesis (and any subsequent performance analysis). Synthesis experiments show the effectiveness of the POR on a set of realistic manufacturing system models.
TL;DR: In this article , the authors propose a methodology for formal synthesis of successful attacks against two well-known protocols, the Alternating Bit Protocol (ABP) and the Transmission Control Protocol (TCP), where the attacker can always eventually win, called For-all attacks.
Abstract: There is an increasing need to study the vulnerability of communication protocols in distributed systems to malicious attacks that attempt to violate properties such as safety or nonblockingness. In this paper, we propose a common methodology for formal synthesis of successful attacks against two well-known protocols, the Alternating Bit Protocol (ABP) and the Transmission Control Protocol (TCP), where the attacker can always eventually win, called For-all attacks. This generalizes previous work on the synthesis of There-exists attacks for TCP, where the attacker can sometimes win. We model the ABP and TCP protocols and system architecture by finite-state automata and employ the supervisory control theory of discrete event systems to pose and solve the synthesis of For-all attacks, where the attacker has partial observability and controllability of the system events. We consider several scenarios of person-in-themiddle attacks against ABP and TCP and present the results of attack synthesis using our methodology for each case.
TL;DR: In this paper , a manufacturing cell in the presence of faults, coming from the devices of the process, is considered and the modular modeling of the subsystems of the cell is accomplished using of appropriate finite deterministic automata.
Abstract: In the present paper, a manufacturing cell in the presence of faults, coming from the devices of the process, is considered. The modular modeling of the subsystems of the cell is accomplished using of appropriate finite deterministic automata. The desired functionality of the cell as well as appropriate safety specifications are formulated as eleven desired languages. The desired languages are expressed as regular expressions in analytic forms. The languages are realized in the form of appropriate general type supervisor forms. Using these forms, a modular supervisory design scheme is accomplished providing satisfactory performance in the presence of faults as well guaranteeing the safety requirements. The aim of the present supervisor control scheme is to achieve tolerance of basic characteristics of the process coordination to upper-level faults, despite the presence of low-level faults in the devices of the process. The complexity of the supervisor scheme is computed.
TL;DR: In this paper , a data-driven deep reinforcement learning framework is proposed for building energy management, where a reinforcement learning supervisory controller is firstly developed and deployed on the building for the heating, ventilation and air conditioning (HVAC) system and monitored for performance degradation by tracking an aggregate metric.
TL;DR: In this article , a data-driven method for monitoring the modes' switching constraints is presented, which is based on state transition matrix and decision-tree methods to discover datadriven mode switching conditions.
Abstract: In a multimode industrial control system, mode switching decisions have to follow standard operating procedures which are set for the safety of the system based on the operating limitations of equipment. A rich literature can be found on monitoring multimode systems. However, that work is mainly focused on mode identification and monitoring anomalies in the process running under each mode. Instead, we present a data-driven method for monitoring the modes’ switching constraints. This article is based on state-transition matrix and decision-tree methods to discover data-driven mode switching conditions. Moreover, our approach is not limited to only threshold based condition learning. To capture data trajectory-based conditions, we adopt a functional data descriptors method. In practical experiments, we showed that our approach can discover anomalous mode-switching decisions which cannot be discovered by previous multimode process-monitoring methods.
TL;DR: In this paper , two new approaches based on the Supervisory Control Theory (SCT) of Discrete Event Systems (DES) are proposed for autonomous navigation of multiple robots with single-robot tasks being assigned by a centralized scheduler.
TL;DR: In this paper , a new custom supervisory system based on Internet of Things (IoT), creating an information sharing environment, was proposed for a micro-grid, composed of a photovoltaic power plant and a storage system.
Abstract: The importance of renewable energies and energy storage system forming a micro-grid and integrating it to the electrical grid is widely spread. A supervisory system plays a crucial role in controlling, managing, and planning the micro-grid. This paper demonstrates the development of a new custom supervisory system based on Internet of Things (IoT), creating an information sharing environment. The proposed supervisory system is based on open-source tools for a micro-grid, composed of a photovoltaic power plant and a storage system, employing smart devices and making non-smart devices compatible with IoT systems. The new supervisory improves the available system by incorporating new features and devices and increasing the data polling rate when necessary. A comparison between the current supervisory system and the proposed one is performed, showing that the new system is more flexible, easily modified, cost-effective, and more fault-resilient.
TL;DR: This problem of synthesizing a reduced smart attack model that is attack equivalent to A with respect to S, can be transformed to a classical supervisor reduction problem, making all existing synthesis tools available for supervisor reduction directly applicable to this problem.
Abstract: In this letter, we investigate how to make use of model reduction techniques to identify the vulnerability of a closed-loop system, consisting of a plant and a supervisor, that might invite attacks. Here, the system vulnerability refers to the existence of key observation sequences that could be exploited by a specific smart sensor attack to cause damage infliction. We consider a nondeterministic smart attack, i.e., there might exist more than one attack choice over each received observation, and adopt our previously proposed modeling framework, where such an attack is captured by a standard finite-state automaton. For a given supervisor S and a smart sensor attack model A, another smart attack model ${\mathrm{ A}}'$ is called attack equivalent to A with respect to S, if the resulting compromised supervisor, defined as the composition of the supervisor S and attack model ${\mathrm{ A}}'$ , is control equivalent to the original compromised supervisor, defined as the composition of S and A. Following the spirit of supervisor reduction that relies on the concept of control congruence, we will show that, this problem of synthesizing a reduced smart attack model ${\mathrm{ A}}'$ that is attack equivalent to A with respect to S, can be transformed to a classical supervisor reduction problem, making all existing synthesis tools available for supervisor reduction directly applicable to our problem. A simplified and ideally minimum-state attack model can reveal all necessary observation sequences for the attacker to be successful, thus, reminds system designers to take necessary precautions in advance, which may improve system resilience significantly. An example is presented to show the effectiveness of our proposed attack model reduction technique.
26 Jan 2022
TL;DR: In this paper , a discrete timed Petri net (DTPN) based supervisory control method is proposed to avoid undesirable states in Cyber-Physical Systems (CPSs) while achieving the goal of production by a specified time constraint.
Abstract: The widely available sensor data from IoT enables the implementation of real-time controllers in factories to efficiently track the progress of production activities and status of resources in the systems. However, failure prone resources or machines in factories frequently lead to negative effects on the performance of production systems. In addition, due to contention of resources involved in different production processes, the Cyber-Physical Systems (CPS) may be brought to undesirable states in which all or parts of the production activities are blocked, in circular waiting or starvation. Recently, there are relevant studies on the impact of resource failures on Cyber-Physical Systems on a discrete timed Petri net (DTPN) model. However, the capabilities to avoid the undesirable states in CPS based on discrete timed Petri nets models are not explored. This paper aims to study the properties of a discrete timed Petri net supervisory control method that can avoid undesirable states while achieving the goal of production by a specified time constraint. These capabilities to avoid the undesirable states in CPS based on DTPN models are characterized by a property. The proposed supervisory control method is illustrated by an example.