Software-Defined Event-Triggering Control for Large-Scale Networked Systems Subject to Stochastic Cyberattacks

A Matlab/Simulink Multi-agent Toolkit for Distributed Networked Fault Tolerant Control System

In this paper a decentralized guaranteed cost control for a class of interconnected large scale networked control system is presented. For this purpose a local state feedback controller is designed for each system. There is high interconnection between each subsystem. The control loop of each subsystem is closed via communication network. Packet Loss, network induced delay and delays at interconnected states are considered in problem formulation. New sufficient conditions for the existence of guaranteed cost controllers are proposed by introducing a Lyapunov-Krasovskii functional. An explicit expression for the desired robust decentralized local state feedback control law is also given. Finally, numerical example shows the efficiency of proposed method in comparison with conventional controls.

In this paper, a robust decentralized feedback control is proposed for large scale networked control systems. Some less conservative sufficient conditions are presented for existence of the robust decentralized feedback controller for large scale networked control system under digital communication to have maximum robustness against admissible time delays, consecutive packet loss, disturbances and interactions between the subsystems. The validity of the proposed method is illustrated by applying it to a load-frequency control problem for a multi-area power system with digital communication. Simulation results show more robustness and performance improvement of the proposed method in comparison with conventional methods.

Numerous efforts are underway to develop testing and experimentation tools to evaluate the performance of networked control systems (NCS) and supervisory control and data acquisition (SCADA) systems. These tools offer varying levels of fidelity and scale. Yet, researchers lack an experimentation framework for systematic testing and evaluation of NCS reliability and security under a wide range of failure scenarios. In this paper, we propose a modular experimentation framework that integrates the NCS semantics with the DETERLab cyber security experimentation facilities. We develop several attack scenarios with realistic network topology and network traffic configurations to evaluate the impact of denial of service (DoS) attacks on scalar linear systems. We characterize the impact of the attack dynamics on six plants located at various levels in a hierarchical topology. Our results suggest that emulation-based evaluations can provide novel insights about the network-induced security and reliability failures in large scale NCS.

The problem of event‐triggered impulsive control (ETIC) for stochastic multi‐agent systems (SMASs) under stochastic cyber attacks is investigated. In a stochastic cyber‐attack model, it is suggested to combine denial‐of‐service (DoS) and deception attacks using two independent Bernoulli random sequences. The event triggering mechanism (ETM) in the ETIC system creates the impulsive control time sequences. It is suggested to use ETMs with waiting times to stop Zeno behavior. Based on the proposed ETMs, sufficient criteria are given for the mean square consensus of SMASs. Two simulation examples are provided to validate our ETIC scheme.

This paper focuses on the hybrid-driven-based ${\mathcal {H}}_{\infty }$ control for networked cascade control systems (NCCSs) with actuator saturations and stochastic cyber attacks. In order to relieve the network bandwidth load effectively, a hybrid triggered scheme is introduced, which contains a switch between time-triggered scheme and event-triggered scheme. A newly hybrid-driven-based NCCS model is established by considering the effects of both actuator saturations and stochastic cyber attack, which is an important threat to network security. By using the Lyapunov stability theory, sufficient conditions are obtained to ensure the system stability. Furthermore, both primary controller gain and secondary controller gain are achieved explicitly in terms of linear matrix inequality techniques. Finally, a power plant gas-turbine system is presented to illustrate the usefulness of the designed state feedback controllers.

A novel Q-learning approach is introduced for the design of a linear adaptive regulator for a large-scale interconnected system. The subsystems communicate with each other through a network. The network induced random delays and data drop out are modeled along with the system dynamics. Stochastic Q-learning is used to estimate the Q-function parameters for the case of periodic and intermittent feedback. The estimated parameters are subsequently used for the regulator design without using value and policy iterations. The asymptotic convergence of the system state vector and bounded ness of the parameter vector is demonstrated using Lyapunov analysis. Further, when the regression vector of the Q-function estimator satisfies the persistency of excitation (PE) condition, the Q-function parameters converge to the expected target values. The analytical design is evaluated using numerical examples via simulation.

Supervisory Control Design for Networked Systems with Time-Varying Communication Delays

In order to ensure the system performance while considering the economic utilization of network resources, this paper investigates the problem of the <i>L₂-L_∞</i> control for a class of distributed-delay networked control systems (NCSs) with model parameter uncertainty under the event-triggered mechanism (ETM). Firstly, a non-fragile state feedback controller model structure with different time-varying parameter matrices is adopted. Secondly, the time-varying delay information combined with the ETM is considered in stability analysis, based on the delay-dependent Lyapunov-Krasovskii functional and the free weight matrix method, sufficient conditions are obtained to guarantee the robust asymptotic stability and the <i>L₂-L_∞</i> performance of the closed-loop system. Then the co-design method of the controller and the ETM is given by using linear matrix inequalities (LMIs). Finally, the feasibility of the co-design scheme is verified by a numerical example and some comparison results. Compared with some existing works, the proposed method leads to larger inter-event transmission intervals, which can save network resources while preserving the desired control performance.

For a class of uncertain continuously networked Lurie control systems with both sensor-to-controller time-delay and controller-to-actuator time-delay, the problem of codesigning its observer and fault-tolerant controller based on an event-triggered mechanism under actuator failure is investigated. Firstly, considering that the state of the system cannot be measured directly, an observer is constructed on the controller node. Secondly, to reduce the waste of network bandwidth resources and improve the performance of the network control system, a network control system approach based on event-triggered mechanism is proposed. By introducing the event-triggered mechanism and the actuator fault indication matrix, the Lurie networked control system is modeled as a Lurie system with time-delay using the state augmentation technique to obtain a model of the closed-loop system. Finally, based on Lyapunov stability theory, sufficient condition for the stability of the closed-loop system is obtained, and the design method of the fault-tolerant controller and the observer is given. The obtained results are given in the form of linear matrix inequalities, which are easy to be solved by using the linear matrix inequality toolbox. Finally, the feasibility and effectiveness of the method are illustrated by a simulation example.

This article presents the design of an event-trigger-based networked robust dissipative tracking control systems. An event-triggered mechanism (ETM) is proposed by introducing the probability density distribution of communication delay. Thus, it can yield less conservative results. The tracking error system is transferred by a distributed communication delay system wherein the delay probability density is viewed as the kernel of the distributed delay. The threshold of the proposed ETM is designed as a dynamic parameter to adapt the transmission of the control signal. By applying the Lyapunov method, sufficient conditions are achieved to ensure the stability of the tracking error system with strictly dissipative performance, which includes <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> performance and passive performance. Based on the dissipativity analysis condition, a co-design method with both tracking control and the ETM is derived in a united framework. Experiments on networked dc motor tracking system are provided to show the effectiveness of the presented method.

This research investigates the design of state feedback controllers for Networked Control Systems (NCSs) subject to actuator failures alongside hybrid cyber‐attacks, specifically Denial‐of‐Service (DoS) and deception attacks. To reduce the use of network resources, two distinct dynamic event‐triggered schemes (DETSs) are proposed. These DETSs govern the data transmission scheduling for both measurement outputs and control inputs across the communication network. A key contribution lies in the simultaneous consideration of actuator malfunctions and the aforementioned hybrid cyber‐attack scenarios. Utilizing Lyapunov stability theory, conditions for the mean square asymptotic stability of the resultant augmented closed‐loop system are established. Subsequently, controller gains and event‐triggering parameters are co‐designed through the application of linear matrix inequality (LMI) techniques. Finally, a simulation example validates the theoretical results, demonstrating the proposed method's efficacy in mitigating the adverse impact of such cyber‐attacks and actuator failures on networked control systems' performance.

In this paper, finite horizon optimal control and communication co-design problem has been investigated for uncertain networked control system (NCS) with limited transmit power. Firstly, the mathematical relation between network imperfections (e.g. network-induced delays and packet dropouts) and practical wireless communication channel quality has been studied. Then, a novel networked control system model has been represented that includes both physical system dynamics and network dynamics. Next, adopting the emerging neuro dynamics programming (NDP) technique and actor-critic-identifier (ACI) architecture, a novel time-based finite horizon optimal control and communication co-design has been proposed. The proposed scheme cannot only learn the optimal co-design within fixed final time, but also relax the requirement of NCS dynamics and satisfy the practical transmit power constraint. The Lyapunov Theorem is used to validate the effectiveness of proposed scheme. With the proper NN weight update law, proposed scheme can ensure all closed-loop signals and NN weights are uniformly ultimately bounded (UUB). Moreover, simulation results are also included to demonstrate the effectiveness of the proposed scheme.

In this article, the dissipativity-based filtering of the Markovian jump neural networks subject to incomplete measurements and deception attacks is investigated by adopting an event-triggered communication strategy, where the attackers are supposed to occur in a random fashion but obey the Bernoulli distribution. Consider that the information of the system mode is transmitted to the filter over the communication network that is vulnerable to external attacks, which may lead to the undesired performance of the resulting system by injecting malicious information from the attackers. As a result, the filter has difficulty completing information from the original system. Besides, an event-triggered communication mechanism is introduced to reduce the communication frequency between data transmission due to the limited network resources, and different triggering conditions corresponding to different jump modes are developed. Then, based on the above considerations, the sufficient condition is derived to ensure the stochastic stability and dissipativity of the resulting augmented system although the deception attacks and incomplete information exist. A numerical simulated example is provided to verify the theoretical analysis.

This paper studies the problem of event-triggered fault detection filter (FDF) and controller coordinated design for a continuous-time networked control system (NCS) with biased sensor faults. By considering sensor-to-FDF network-induced delays and packet dropouts, which do not impose a constraint on the event-triggering mechanism, and proposing the simultaneous network bandwidth utilization ratio and fault occurrence probability-based event-triggering mechanism, a new closed-loop model for the considered NCS is established. Based on the established model, the event-triggered H ∞ performance analysis, and FDF and controller coordinated design are presented. The combined mutually exclusive distribution and Wirtinger-based integral inequality approach is proposed for the first time to deal with integral inequalities for products of vectors. This approach is proved to be less conservative than the existing Wirtinger-based integral inequality approach. The designed FDF and controller can guarantee the sensitivity of the residual signal to faults and the robustness of the NCS to external disturbances. The simulation results verify the effectiveness of the proposed event-triggering mechanism, and the FDF and controller coordinated design.