As a specific kind of cyber–physical systems (CPSs), autonomous robot clusters play an important role in various intelligent manufacturing fields. However, due to the increasing design complexity of ...robot clusters, it is becoming more and more challenging to guarantee the safety and efficiency for multirobot cooperative navigation in dynamic and complex environments. Although deep reinforcement learning (DRL) shows great potential in learning multirobot cooperative navigation policies, existing DRL-based approaches suffer from scalability issues and rarely consider the transferability of trained policies to new tasks. To address these problems, this article presents a novel DRL-based multirobot cooperative navigation approach named HRMR-Navi that equips each robot with both a two-layered hierarchical graph network model and an attention-based communication model. In our approach, the hierarchical graph network model can efficiently figure out hierarchical relations among all agents that either cooperate for efficiency or avoid obstacles for safety to derive more advanced strategies, and the communication model can accurately form a global view of the environment for a specific robot, thus, the multirobot cooperation efficiency can be further strengthened. Meanwhile, we propose an improved proximal policy optimization (PPO) algorithm based on the Maximum Entropy Reinforcement Learning, named MEPPO, to enhance the robot exploration ability. Comprehensive experimental results demonstrate that, compared with state-of-the-art approaches, HRMR-Navi can achieve more efficient cooperative navigation with less time cost, lower collision rate, higher scalability, and better knowledge transferability.
This article is concerned with the distributed confidentiality fusion estimation problem for cyber-physical systems in the presence of eavesdroppers. A novel active contamination strategy is proposed ...to guarantee the confidentiality of local state estimates (LSEs) that are transmitted to the fusion center (FC) over communication channels. Here, the LSEs are actively contaminated by the contaminating vectors, which are related to the weighting fusion process. Meanwhile, the selecting matrices that denote whether the components are contaminated are, respectively, designed for linear and nonlinear systems by maximizing the mean square errors of eavesdropper's estimator. Under this contamination strategy, the confidentiality of systems can be effectively guaranteed when the eavesdropper tries to obtain the real state by fusing the contaminated estimates, because the estimation error covariance of the eavesdropper is large. At the same time, the corresponding compensation strategy is employed in the FC to compensate the performance loss caused by the proposed contamination method. Finally, two illustrative examples are exploited to demonstrate the effectiveness of the proposed methods.
Current mass individualisation and service-oriented paradigm calls for high flexibility and agility in the warehouse system to adapt changes in products. This paper proposes a novel digital ...twin-driven joint optimisation approach for warehousing in large-scale automated high-rise warehouse product-service system. A Digital Twin System is developed to aggregate real-time data from physical warehouse product-service system and then to map it to the cyber model. A joint optimisation model on how to timely optimise stacked packing and storage assignment of warehouse product-service system is integrated to the Digital Twin System. Through perceiving online data from the physical warehouse product-service system, periodical optimal decisions can be obtained via the joint optimisation model and then fed back to the semi-physical simulation engine in the Digital Twin System for verifying the implementation result. A demonstrative prototype is developed and verified with a case study of a tobacco warehouse product-service system. The proposed approach can maximise the utilisation and efficiency of the large-scale automated high-rise warehouse product-service system.
Sensitivity analysis is fundamental and essential in the analysis and design of any system. Sensitivities are usually defined as derivatives of system variables or system performance with respect to ...its parameters. This paper discusses a sensitivity analysis method for a class of cyber-physical systems. We consider the following system as a class of cyber-physical systems at the first step of the research: a hybrid system in which a continuous-time system and a discrete-time system are connected through A/D and D/A interfaces. They are represented by block diagrams in which arbitrary elements including nonlinear elements are arbitrarily connected. It is known that the sensitivity analysis based on Tellegen's theorem has become a standard method for electric circuits. We extend Tellegen's theorem to the hybrid system and drive a method for computing sensitivities of any signal with respect to any parameter in the system. We also propose a method to apply the proposed method to parameter optimization of the systems. In order to evaluate the performance of the proposed method, some numerical experiments are conducted. We apply the proposed method to a cyber-physical system whose parameter sensitivities can be derived analytically in order to estimate its accuracy. It is shown through numerical experiments that the proposed method can obtain sensitivities with sufficient accuracy. Furthermore, we apply it to an optimization problem of a continuous and discrete-time hybrid system. It is shown that the proposed method makes it possible to obtain optimal parameters as the hybrid system.
Though recent advancements in dc microgrids are largely based on distributed control strategies to enhance reliability and scalability, the absence of a centralized controller to check the global ...information makes these schemes highly susceptible to cyber attacks. Since false data injection attacks (FDIAs) are considered as a prominent attack methodology in dc microgrids, prior emphasis is usually laid on compromised sensors and controllers only related to dc voltages. Hence, this article first segregates the FDIAs on the output currents into destablization and deception attacks, based on the modeling of attack elements with respect to the consensus theory. Second, a discordant element based detection approach is designed to detect the attacked nodes accurately, using an extended analysis of the cooperative control network. A risk assessment framework for dc microgrids against cyber attacks is provided alongside all the case studies. An evaluation theory is also presented to assist the proposed detection scheme to differentiate between cyber attacks and faults. Further, the proposed detection approach is theoretically verified and validated using simulation and experimental conditions.
Industrial control systems (ICSs) are transitioning from legacy-electromechanical-based systems to modern information and communication technology (ICT)-based systems creating a close coupling ...between cyber and physical components. In this paper, we explore the ICS cybersecurity landscape including: 1) the key principles and unique aspects of ICS operation; 2) a brief history of cyberattacks on ICS; 3) an overview of ICS security assessment; 4) a survey of "uniquely-ICS" testbeds that capture the interactions between the various layers of an ICS; and 5) current trends in ICS attacks and defenses.
In today’s competitive environment of Industry 4.0, cyber-physical systems (CPS) of various advanced manufacturing paradigms have brought new challenges to maintenance managements. Efficient ...prognostics and health management (PHM) policies, which can integrate both individual machine deteriorations and different manufacturing paradigms, are urgently needed. Newly proposed PHM methodologies are systematically reviewed in this paper: as the decision basis, an operating load based forecasting algorithm is proposed for machine health prognosis; at the machine level, a dynamic multi-attribute maintenance model is studied for diverse machines in CPS; at the system level, novel opportunistic maintenance policies are developed for complex flow-line production, mass customization and reconfigurable manufacturing systems, respectively. This framework of PHM methodologies has been validated in industrial implementations.
In this paper, a novel event-triggered control strategy is proposed for cyber-physical systems (CPSs) with disturbance and measurement noise under two channels asynchronous denial-of-service (DoS) ...attacks. Two different event-triggering mechanisms for the sensor-to-controller (S-C) channel and controller-to-actuator (C-A) channel are designed, and the relationship amongst the event-triggering coefficients is obtained. Then sufficient conditions on the duration and frequency of the DoS attacks are proposed to guarantee the input-to-state stability of the closed-loop system under DoS attacks based on an observer-based control framework. In contrast to the existing studies where the synchronous DoS attacks on the S-C and C-A channels or attacks only on one channel are considered, the coupling problem for the two interconnected channels under asynchronous DoS attacks is solved. Furthermore, the condition for removing the restriction of the buffer size is obtained. Finally, a numerical simulation is given to illustrate the efficiency and the feasibility of the proposed strategy.
Household-level distributed energy sources, such as rooftop photovoltaic, microturbines, and energy storage, become important behind-the-meter (BTM) resources. BTM resources can meet all or part of ...users' demands. Establishing a peer-to-peer (P2P) energy trading network among these users will further promote the utilization of BTM resources. However, such a proposal faces the problem that cyber trading and physical dispatching are difficult to coordinate. Therefore, this paper proposes the architecture of the behind-the-meter peer-to-peer (BTM-P2P) energy trading system, including the cyber layer and physical layer. To ensure that users strictly execute the cyber trading results in the physical layer, a trading mechanism considering credit is designed, and the user's credit has an impact on the bidding priority, which in turn urges the user to strictly execute in subsequent tradings. Then, a light blockchain suitable for energy trading is developed, ensuring that both the trading results and the actual dispatching results are not tampered with. Database technology is inserted in the light blockchain to improve efficiency. Finally, a BTM-P2P cyber-physical testbed coupling physical dispatching with cyber trading is built, providing technical support for the implementation of BTM-P2P.
Automotive cyber-physical systems need to be rigorously checked and tested under various physical conditions. Automakers aim to improve development efficiency of the automotive cyber-physical systems ...in the fierce market competition. However, the actual development process suffers from the challenges of long development cycle and poor scalability. To tackle these challenges, this article develops a digital twinning based adaptive development environment for automotive cyber-physical systems, which addresses two critical problems: each physical entity (i.e., electronic control unit, component, test source, etc.) needs to clone a corresponding digital twin; digital twins and the physical entities need to interact closely. The first problem is addressed through proposing an integrated digital twinning clone flow. The second problem is addressed through developing a smart digital twinning board. Our case study with the automotive body control system demonstrates that the adaptive development environment achieves a high adaptability with short development cycle, low complexity, low cost, high scalability, and high flexibility, which meet various automotive cyber-physical design requirements during the development process.
