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"distributed control"
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Blockchain and Random Subspace Learning-Based IDS for SDN-Enabled Industrial IoT Security
The industrial control systems are facing an increasing number of sophisticated cyber attacks that can have very dangerous consequences on humans and their environments. In order to deal with these issues, novel technologies and approaches should be adopted. In this paper, we focus on the security of commands in industrial IoT against forged commands and misrouting of commands. To this end, we propose a security architecture that integrates the Blockchain and the Software-defined network (SDN) technologies. The proposed security architecture is composed of: (a) an intrusion detection system, namely RSL-KNN, which combines the Random Subspace Learning (RSL) and K-Nearest Neighbor (KNN) to defend against the forged commands, which target the industrial control process, and (b) a Blockchain-based Integrity Checking System (BICS), which can prevent the misrouting attack, which tampers with the OpenFlow rules of the SDN-enabled industrial IoT systems. We test the proposed security solution on an Industrial Control System Cyber attack Dataset and on an experimental platform combining software-defined networking and blockchain technologies. The evaluation results demonstrate the effectiveness and efficiency of the proposed security solution.
Journal Article
Window Impulsive Consensus of Time‐Varying Multi‐Agent Systems Under Deception Attacks on Time Scales
This paper addresses the consensus problem for time‐varying multi‐agent systems (MASs) under deception attacks on time scales. A novel hybrid control strategy is proposed, integrating sampled‐data feedback with time‐varying window impulsive control, which eliminates the conventional requirement of preset fixed impulsive instants. To characterize deception attacks on transmission channels, Bernoulli‐distributed random variables are introduced to model the occurrence and probability of attacks. Moreover, average parameters related to impulsive gains and time‐varying window boundaries are incorporated into the design. Based on time‐scale theory and Lyapunov stability analysis, sufficient conditions are derived for achieving both leader‐following consensus and dynamic average consensus. These conditions, which depend on the average parameters, not only relax the constraints on impulsive gains but also reduce the required frequency of impulsive control inputs. The effectiveness of the proposed control scheme is validated through numerical simulations.
Journal Article
Overview of Consensus Protocol and Its Application to Microgrid Control
Different control strategies for microgrid applications have been developed in the last decade. In order to enhance flexibility, scalability and reliability, special attention has been given to control organisations based on distributed communication infrastructures. Among these strategies, the implementation of consensus protocol stands out to cooperatively steer multi-agent systems (i.e., distributed generators), which is justified by its benefits, such as plug and play capability and enhanced resilience against communication failures. However, as the consensus protocol has a long trajectory of development in different areas of knowledge including multidisciplinary subjects, it may be a challenge to collect all the relevant information for its application in an emerging field. Therefore, the main goal of this paper is to provide the fundamentals of multi-agent systems and consensus protocol to the electrical engineering community, and an overview of its application to control systems for microgrids. The fundamentals of consensus protocol herein cover the concepts, formulations, steady-state and stability analysis for leaderless and leader-following consensus problems, in both continuous- and discrete-time. The overview of the applications summarises the main contributions achieved with this technique in the literature concerning microgrids, as well as the associated challenges and trends.
Journal Article
Modeling of Distributed Control System for Network of Mineral Water Wells
The article is devoted to solving the problem of designing a distributed control system for a network of production wells on the example of mineral water deposits in the Caucasus Mineral Waters region, Russia. The purpose was to determine the set of parameters of the control system to ensure technologically effective and safe operating modes of mineral water deposits. A mathematical model of the deposit was developed taking into account the given configuration and production rate of the network of the wells. The detailed algorithm is presented for designing the control system under consideration based on the frequency concept of analysis and synthesis for distributed control systems. The experimental tests and model validation were performed at the production wells facility of “Narzan”, Kislovodsk, Russia. The results of modeling and field experiments confirmed the adequacy of the mathematical model and the effectiveness of the proposed algorithm. The authors came to the conclusion that the adapted mathematical model can be used to create a regional automated field cluster management system for monitoring, operational management and forecasting the nature of real hydrogeological processes and ensuring their stability.
Journal Article
Distributed containment control of second-order multi-agent systems with inherent non-linear dynamics
This study considers the distributed containment control problem of second-order multi-agent systems with inherent non-linear dynamics. Two distributed control protocols with, respectively, static and adaptive control gains are proposed to ensure that the states of the followers asymptotically converge to the convex hull spanned by the corresponding states of the leaders. For the static control protocol, undirected and directed interaction topologies among the followers are taken into consideration, under which sufficient conditions on the control gains are obtained by using a Lyapunov-based approach. For the adaptive control protocol, it is proved that the containment control problem can be solved without requiring any global information if the interaction topology among the followers is undirected. Numerical examples are provided to demonstrate the effectiveness of our theoretical results.
Journal Article
A distributed control method for flexible robotic fish based on PDE
At present, research on flexible robotic fish has become a hot topic. Here, a novel dynamic model of flexible robotic fish is established, and a new control method for flexible robotic fish is proposed. Based on the Hamilton principle, the dynamic model of the flexible robotic fish is established by a partial differential equation, which obtains the relationship between the motion law and the force of the flexible robotic fish. The proposed control method produces the practical motion of flexible robotic fish along with any reference motion of flexible robotic fish, and it is proven that the attitude error is stable in a certain range by using the Lyapunov direct method and simulation. Control parameters are explored to reflect the influence on the control effect. For robotic fish, simulation results indicate that the proposed method can generate more than 10% greater propulsive force than some kinds of traditional control methods and improve the forward propelling efficiency of robotic fish.
Journal Article
A Hybrid EV Charging Approach Based on MILP and a Genetic Algorithm
Uncoordinated electric vehicle (EV) charging can significantly complicate power system operations. In this paper, we develop a hybrid EV charging method that seamlessly integrates centralized EV charging and distributed control schemes to address EV energy demand challenges. The proposed method includes (1) a centralized day-ahead optimal scheduling mechanism and EV shifting process based on mixed-integer linear programming (MILP) and (2) a distributed control strategy based on a genetic algorithm (GA) that dynamically adjusts the charging rate in real-time grid scenarios. The MILP minimizes energy imbalance at overloaded slots by reallocating EVs based on supply–demand mismatch. By combining full and minimum charging strategies with MILP-based shifting, the method significantly reduces network stress due to EV charging. The centralized model schedules time slots using valley-filling and EV-specific constraints, and the local GA-based distributed control adjusts charging currents based on minimum energy, system availability, waiting time, and a priority index (PI). This PI enables user prioritization in both the EV shifting process and power allocation decisions. The method is validated using demand data on a radial feeder with residential and commercial load profiles. Simulation results demonstrate that the proposed hybrid EV charging framework significantly improves grid-level efficiency and user satisfaction. Compared to the baseline without EV integration, the average-to-peak demand ratio is improved from 61% to 74% at Station-A, from 64% to 80% at Station-B, and from 51% to 63% at Station-C, highlighting enhanced load balancing. The framework also ensures that all EVs receive energy above their minimum needs, achieving user satisfaction scores of 88.0% at Stations A and B and 81.6% at Station C. This study underscores the potential of hybrid charging schemes in optimizing energy utilization while maintaining system reliability and user convenience.
Journal Article
Controller Hardware-in-the-Loop Simulation of SOFC-GT Hybrid System
The solid oxide fuel cell–gas turbine (SOFC-GT) hybrid system is confronted with challenges related to system integration and coordinated control. In this study, a Controller Hardware-in-the-Loop Simulation (C-HILS) platform is constructed to validate its digital solutions. The C-HILS platform integrates the Advanced Process Simulation System (APROS), LabVIEW 2020 programming software, NI PXI hardware, and a distributed control system (DCS). Specifically, bidirectional data transmission between the simulation software and the DCS is facilitated through LabVIEW and PXI, leveraging the OLE for Process Control (OPC) protocol and physical Input and Output (I/O) channels. The dynamic SOFC-GT model developed in APROS demonstrates good consistency with design values, with relative errors below 4%. The DCS configuration employs PID controllers to achieve control over total power, SOFC fuel utilization, and gas turbine rotational speed. Experiments under transient conditions reveal that, despite discrepancies in dynamic responses between C-HILS and full-digital simulations, both can achieve stable control. This C-HILS platform effectively integrates virtual models with physical hardware, offering a reliable environment for verifying SOFC-GT control strategies and digital solutions, and thus facilitating the digital transformation of energy systems.
Journal Article