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This paper delves into the output feedback control of systems with dual multi‐memoryless channels, where the data packets transmitted from the sensor to the controller (S/C) and from the controller to the actuator (C/A) are suffered from two different multi‐parallel Markovian fading channels. Two new multi‐state Markovian chains are introduced, by which the multiple fading channels system is transformed into a new jumping parameter system. Then a stochastic maximum principle is given along with an optimal state feedback controller for the case that the state is known. When the state is unknown, a Markov jump linear estimator is designed by using the completing square method. In this case, an output feedback controller is obtained by substituting the real system state with its estimation. Meanwhile, the separation principle is shown. Finally, the validity of these methods is verified by simulation examples. [ABSTRACT FROM AUTHOR]

This paper focuses on the optimal output‐feedback control and stabilization of a networked control system, where both time delay and packet loss are involved. Different from most previous work, the packet loss is Markovian, and the time delay occurs between the actuator and controller. The difficulty is rooted in the failure of the separation principle. The main tools are solving the delayed forward‐backward stochastic difference equations (D‐FBSDEs) and convergent analysis. Resorting to solving D‐FBSDEs and completing the square, we acquire the analytical solution, including the necessary and sufficient solvability condition and the explicit controller, of the finite‐horizon optimal control problem. Based on the finite‐horizon result and convergent analysis, we then obtain the analytical solution of the infinite‐horizon optimal control and stabilization problems. In addition, by analyzing the convergence of the optimal estimator, we establish a constraint relationship between the packet loss probability q$$ q $$ and the system matrix A$$ A $$. The results are evaluated by numerical examples. [ABSTRACT FROM AUTHOR]

Abstract The purpose of this article is to develop the receding horizon (RH) estimation for multi‐rate sampled systems with measurement delays and packet losses in the measurements. An event‐triggered transmission scheme is introduced to remove measurements that are unnecessary for the design of the estimator. The stochastic diagonal matrixes are introduced to represent the phenomenon of packet losses, where each component is subject to an individual Bernoulli process. The original system is firstly transformed into a delay‐free one by using the reorganized observation method. Further, a batch form and an iterative form of RH estimation are proposed by minimizing a given cost function that includes some terminal weighting terms based on the new system. The stability of the proposed RH estimation is guaranteed by the natural assumptions and a simulation instance is given to verify the effectiveness of the proposed method.

This article addresses the problem of designing an event‐triggered fault detector within a networked nonlinear system described by a Takagi–Sugeno (T–S) fuzzy model, accounting for time‐varying delays and denial‐of‐service (DoS) attacks characterized by a binary Markov chain. Our focus is on constructing an event‐triggered residual system, which aims to detect malfunctions in the original fuzzy system while optimizing communication resource allocation. Specifically, it is tailored to combat DoS attacks in the event generator‐to‐fault detector channel and mitigate network‐induced time‐varying delays. Utilizing the Lyapunov–Krasovskii function approach, we formulate linear matrix inequalities to establish the necessary conditions ensuring the asymptotic mean‐square stability of the residual system, meeting a predefined H∞$$ {H}_{\infty } $$ performance criterion. Finally, the simulation results are presented to validate the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

This article addresses the problem of model predictive control of networked jump systems in the presence of DoS attacks and time delays. In the structural framework of the network predictive control system, we mathematically model the networked jump system by using Markov chains to describe the time delays and a polytope model to describe the jump system phenomenon, considering the properties of DoS attacks and time delays. Based on this, we propose a strategy to lessen the effect of network constraints on the control performance of the system. This strategy involves the corresponding control inputs from the control sequence for real‐time active compensation. It includes adjusting the control sequence application length variation based on the duration of the DoS attacks and time delays at each moment. In addition, we demonstrate the recursive feasibility of the control strategy and the global asymptotic stability of the control system from a theoretical perspective through the Lyapunov stability theory. Finally, the effectiveness of the proposed strategy is verified by simulation arithmetic. [ABSTRACT FROM AUTHOR]

The integration of cyber (network) with physical world is a big step in cyber-physical systems. This has revolutionised many industries. But this transformation has made cyber-physical systems vulnerable to attacks. One particular type of attack is the adversarial false data injection which injects false data in either the sensor measurements or the corresponding communication channel. A better understanding of how false data injection (FDI) attacks are constructed is crucial for developing strategies to protect against such attacks. In this paper, we consider two models for networked control systems and present an algorithm for constructing FDI attacks in each case and compare with an existing approach. The conditions for the attack to remain stealthy for systems equipped with a $ \chi ^2 $ χ 2 failure detector and the design of attack vectors that satisfy these conditions are discussed in detail. The algorithms are demonstrated by developing FDI attacks for two real-world examples. [ABSTRACT FROM AUTHOR]

This paper investigates the issue of observer-based dual-dynamic event-triggered scheme into networked control systems, focusing on its application to motion robots. Firstly, it establishes a mathematical model of the motion robot system based on Newtonian mechanics. Secondly, it introduces a dynamic event-triggering mechanism coupled with observer design to minimize data transmission and enhance communication efficiency. Thirdly, it implements a second dynamic event-triggering protocol for controller design, ensuring a positive lower bound for triggering event intervals, thus avoiding Zeno behavior. Fourthly, it constructs a Lyapunov function with internal dynamic variables for stability analysis using linear matrix inequalities. Finally, simulation studies validate the method's efficacy for motion robot systems. [ABSTRACT FROM AUTHOR]

The purpose of this article is to develop the receding horizon (RH) estimation for multi‐rate sampled systems with measurement delays and packet losses in the measurements. An event‐triggered transmission scheme is introduced to remove measurements that are unnecessary for the design of the estimator. The stochastic diagonal matrixes are introduced to represent the phenomenon of packet losses, where each component is subject to an individual Bernoulli process. The original system is firstly transformed into a delay‐free one by using the reorganized observation method. Further, a batch form and an iterative form of RH estimation are proposed by minimizing a given cost function that includes some terminal weighting terms based on the new system. The stability of the proposed RH estimation is guaranteed by the natural assumptions and a simulation instance is given to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

With the increasing utilisation of information technology and artificial intelligence in practical control systems, particularly in large-scale distributed networked systems, growing concerns have arisen regarding the potential disclosure of individuals' sensitive information to adversaries. Consequently, safeguarding privacy security against the rapidly increasing risk of privacy leakages has become a top priority in modern control systems. This survey aims to offer a comprehensive review of privacy-preserving control and filtering problems in networked control system. First, we review some basic introductions to the privacy-preserving mechanisms from the perspective of control community. Then, we present recent advancements in the design of privacy-preserving strategies for various control and filtering problems. Moreover, several possible future research topics are outlined on the privacy-preserving issue of control systems. [ABSTRACT FROM AUTHOR]

Summary: An adaptive event‐triggered scheme is considered for networked control systems subject to deception and reply cyber attacks. In particular, the adaptive event‐triggered mechanism is used in the closed‐loop controller design to reduce signal transmission and communication burden. The attacker destroys the system's performance by employing deception attacks on sensor‐to‐controller communication channels and replay attacks on controller‐to‐actuator communication channels, respectively. By utilizing the Lyapunov stability approach, the closed‐loop system guarantees mean square stability and ensure security. The adaptive event‐triggered controller gains are presented by solving a set of matrix inequalities. Finally, a simulation result including the model of a batch reactor is presented to demonstrate the efficiency of the methods proposed. [ABSTRACT FROM AUTHOR]

This paper concerns an event-triggered H∞ predictive control scheme for a networked control system in which sensor and actuator saturation as well as external disturbances are involved. In the scheme, a state estimator is firstly designed to acquire state estimations from the saturated output with measurement noises. An event generator is given to pick out necessary state estimations for saving feedback channel transmission resources. Furthermore, a buffer-based predictive controller is constructed to compensate for network-induced delays and lighten the communication burden of forward channel networks. Then a co-design criterion is shown to find estimator and controller parameters for the resulting closed-loop system with desired H∞ performance. An inverted pendulum model is employed in numerical simulation to verify the proposed control scheme.

For the problem of fault-tolerant control of non-linear repetitive systems with quantized error, an iterative learning fault-tolerant controller scheme with a logarithmic quantizer is constructed in this paper. Compared with the existing approaches of observer-based fault-tolerant control, the proposed iterative learning observer scheme improve the fault-tolerant control performance in the current iteration by considering the state estimation and fault estimation of the previous iteration, as well as the control error results. Meanwhile, the designed fault-tolerant controller is stable and convergent. Finally, the theoretical results are verified by numerical examples and the relationship between quantized density and controller performance is analysed. [ABSTRACT FROM AUTHOR]

Networked control system (NCS) is widely used in various fields, but the nonlinear of the controlled plants and the limited network bandwidth bring stability issues, which will affect the performance or even instability of the NCS. To address these aforementioned challenges, this paper proposes a novel nonlinear NCS framework, by considering network‐induced delay, adaptive event‐triggered mechanism, state quantization, control input quantization, and external disturbance based on T‐S fuzzy model. Also, based on this framework, we derive an H∞$$ {H}_{\infty } $$ stability criterion for NCS using linear matrix inequality and propose a collaborative design method for event triggers and controllers. Finally, we verify the superiority and effectiveness of the method by giving two numerical examples. [ABSTRACT FROM AUTHOR]

This paper presents an event-triggered sliding mode fault-tolerant control method for networked control systems with actuator faults and external disturbance. First, an event-triggered scheme in the networked control systems is proposed to reduce the number of data transmission. In addition, considering the event-triggering, a sliding mode surface based on the system structure is constructed. Besides, to obtain the controller parameters that meet the H ∞ performance, the bounded real lemma in the form of linear matrix inequality is obtained using the Lyapunov functional. In addition, a sliding mode fault-tolerant control is designed to guarantee that the system can still run stably under the condition of faults and disturbances. Finally, the simulation results of gas turbine system are given to verify the feasibility of the theoretical method. [ABSTRACT FROM AUTHOR]

Integrating a photovoltaic (PV) microgrid system with wireless network control heralds a new era for renewable energy systems. This fusion capitalizes on the strengths of photovoltaic technology, leveraging solar energy for electricity generation while incorporating advanced networked control capabilities. Although employing network communication to facilitate information exchange among system elements offers benefits, it also introduces novel challenges which can hinder fault diagnosis, such as packet loss and communication delay. This paper focuses on a cloud-based fault detection approach for an effective boost converter within a photovoltaic system. Faults are diagnosed using a detection algorithm based on the Lyapunov function, ensuring power optimization. The effectiveness of our approach is demonstrated through simulations of a PV generator model utilizing real-time weather data collected in Brazil, illustrating its robustness through the acquired results. [ABSTRACT FROM AUTHOR]

In this paper, a model predictive control scheme is developed for networked interval type-2 (IT-2) Takagi–Sugeno (T–S) fuzzy systems. To prevent the excessive use of bandwidth, the controller is designed in an event-trigger manner. However, the event conditions often require the transmission of all system states, imposing a substantial demand on network bandwidth; on the other hand, they are subject to network delay and packet loss. For this reason, in the existing approaches, event-triggered mechanisms primarily deployed in close proximity to the plant, or observer-based structures are used to enhance flexibility for implementing the controller. However, a common limitation in all these solutions is the assumption of network links being ideal, or at the very least, not accounting for all network-related limitations. The occurrence of faults is also an inevitable factor that has been overlooked in most related methods. To resolve this issue, a more comprehensive framework for event-triggered controllers is proposed in this paper in which an adaptive fuzzy observer is embedded, and the effects due to delay and packet loss are included in this observer. In addition, by developing an adaptive fault estimator and the introduction of a compensator term into the observer and controller formulations, a fault-tolerant performance of the event-triggered mechanism along with the controller is provided. These features enable the possibility of implementing the event-triggered mechanism next to the controller and at any desired distance from the plant, which resolves a serious concern in this area. Another important challenge considered in this work is ensuring the optimal performance of the controller in the entire prediction horizon. Also, the stochastic stability of the closed-loop system is proved such that defined H 2 and H ∞ performance indices are satisfied. Finally, the proposed control approach is evaluated using numerical and practical examples. [ABSTRACT FROM AUTHOR]

In a Networked Control System (NCS), event-triggering is often used to reduce the number of network transmission instances and improve network usage. This paper considers transmitting output data rather than the estimated state for such event-triggered schemes. Output transmission facilitates efficient transmission by reducing the size of the packets sent over the network. However, since the state observer utilizes delayed information output transmission deteriorates system performance and requires improved observer-based prediction schemes for closed-loop control. The performance of a new scheme involving the transmission of sequential output information in a single packet to improve the state observer's performance is demonstrated in this paper. A sequential observer is constructed that uses successive output information to better observe the states, and a prediction scheme is used to take care of the delays due to event-triggering, network delays, and dropouts. Further, event-triggering is employed in both the feedback and forward channels. The demonstrated efficacy of this sequential approach in the networked control of an inverted pendulum system and a DC motor system emphasizes its potential as a practical solution for improved control in NCSs, particularly in the face of network constraints and communication challenges. • The work deals networked control systems with the resource constrained communication network by incorporating event-triggering in both the feedback and forward paths. • Using a predictive control method, the network delays and dropouts, and the dropouts due to event-triggering are dealt with. • A new sequential observer is constructed to process sequential output information at the remote end for improving the state estimates. • The proposed observer reduces the communication load considerably while effectively exploiting the packet size in the network. [ABSTRACT FROM AUTHOR]

This paper deals with the design problem of networked cascade control systems (NCCSs) with two different event‐triggered mechanisms (ETMs) for the feedback loops. A combination of stochastic denial‐of‐service (DoS) attack and deception attack has been considered for the communication network. To comply with the practical point of view, the primary and the secondary systems have been considered with distinct disturbances. First, the closed‐loop system with state feedback controllers is provided in a unified stochastic delayed system. Then, the Lyapunov–Krasovskii stability theory and stochastic analysis techniques are employed to derive and formulate H∞$$ {\mathcal{H}}_{\infty } $$ control design conditions in terms of linear matrix inequalities (LMIs). Finally, a superheater steam temperature control is utilized to assess the applicability of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is concerned with the nonfragile predictive control problem for the networked control system (NCS) with input delay and network-induced time delays (NITDs). First, the transmission strategy governed by redundant channels is introduced to reduce the occurrence of data packet dropout between the sensor and the observer. Moreover, the event-triggered mechanism (ETM) is employed to save the network resources, where the maximum triggered interval is given. Subsequently, a nonfragile networked predictive control scheme (NPCS) is designed to address the input delay and the NITDs. Accordingly, the sufficient criterion ensuring mean-square exponential stability (MSES) is derived by employing the Lyapunov–Krasovskii stability theorem. Both the observer gain matrix (OGM) and the controller gain matrix (CGM) are gained through solving the nonlinear minimization problem with convex constraints. Finally, a simulation example is utilized to demonstrate the usefulness of the proposed main results. [ABSTRACT FROM AUTHOR]

In actual operation, there are security risks to the data of the network control system, mainly in the form of possible eavesdropping of signals in the transmission channel and parameters in the controller leading to data leakage. In this paper, we propose a scheme for encrypting linear controllers using fully homomorphic encryption, which effectively removes these security risks and substantially improves the security of networked control systems. Meanwhile, this paper uses precomputation to handle data encryption, which eliminates the encryption time and solves the drawback of fully homomorphic encryption that it is difficult to apply due to the efficiency problem. Compared to previous schemes with precomputation, for the first time, we propose two methods to mitigate the problem of the slight security degradation caused by precomputation, which makes our scheme more secure. Finally, we provide numerical simulation results to support our scheme, and the data show that the encrypted controller achieves normal control and improves safety and efficiency. [ABSTRACT FROM AUTHOR]

This paper concerns an event-triggered control for uncertain linear systems with process time-varying delays. An adaptive event trigger (AET) is employed for reducing the data transmission amount from the sensor to the controller. Because a positive constant and a positive variable are simultaneously involved in the AET, the AET condition may be difficult to be violated and the data transmission amount may be reduced. A discrete-time feedback control law is employed to guarantee the uniformly ultimately bounded (UUB) of the closed-loop systems. If the gain matrix of the time-delayed state is compromised with the sufficient stability condition, the desired stability can be always achieved regardless of the time-varying delays. In addition, the bound region can be specified by regulating the threshold of the AET. It is proved that the unwanted Zeno phenomena is naturally excluded since the minimal event-triggered time-interval of the AET is a positive real number. Furthermore, the maximal event-triggered time interval can also be quantitatively approximated. A numerical example is provided to demonstrate the effectiveness of the proposed method, and the influences of the AET threshold and time delay are discussed as well. [ABSTRACT FROM AUTHOR]

This paper studies the networked control system (NCS) with semi-Markov topology switching and network delay. The time delays of the system are considered in the measurement and control channels. The control channel is between the controller and the actuator, the measurement channel is between the sensor and the controller. The topology switching and the transition process among modes are described by semi-Markov sojourn-time probability density function and Markov transition probability matrix respectively. The mean square stability conditions for the networked multi-LSRMs system are obtained by constructing a new Lyapunov function. To ensure the σ -error mean square stability of the closed loop system, a state feedback controller is designed by combining the variation technique of inequalities and Lyapunov stability theory. Finally, several experiments results verify the effectiveness and rationality of the proposed control strategy. • Mathematical modeling of networked semi-Markovian topological switching systems with time delay. • The stability of semi-Markovian jump system is analyzed, and the σ -error mean square stability conditions are presented. • A dual-mode feedback controller is designed based on system topology switching and time delay. • The effectiveness of the proposed control strategy is demonstrated through a multi linear switched reluctance motors system. [ABSTRACT FROM AUTHOR]

In this paper, the problems of modeling and sliding mode control for a class of nonlinear discrete networked cascade control systems (NCCSs) are studied. Firstly, a class of discrete networked cascade control systems with nonlinear disturbance is considered, the sliding mode control is introduced and the model of the system is established. Based on this model and the Lyapunov functional method, the state feedback primary controller and the sliding mode secondary controller for this system are co-designed. Finally, an example of a thermal power plant is given to illustrate the effectiveness of the proposed co-design method. The main advantages are that the sliding mode control is introduced into cascade control system (CCS) and the design method of sliding mode controller for this system is proposed for the first time. On the premise of ensuring the stability of the system, it can be driven to the sliding mode surface in a limited time, and remain on the sliding mode surface in all subsequent times. The method can achieve better results and be applied to the corresponding industrial system with networked cascade control structure. [ABSTRACT FROM AUTHOR]

This article proposes an event‐triggering mechanism (ETM)‐based security control strategy for an uncertain networked control system (NCS) to cope with jamming attacks on multiple transmission channels. A structure of the system control block for the attacked uncertain NCS is constructed and a virtual system is designed to cope with the mismatched parametric uncertainty and derive both the optimal control gain and the virtual control gain. Under multiple wireless channels jamming attack, an optimal jamming attack strategy that maximizes the attack power from the attacker's point of view is engineered. Furthermore, an ETM‐based control strategy with jamming parameters is designed to ensure the input‐to‐state stability of NCS under uncertainty and jamming attacks. Finally, the numerical simulation results show the effectiveness of the control algorithm in this article. [ABSTRACT FROM AUTHOR]

The Network Control System, which includes three different nodes connected through a band-limited real-time digital network, was created as a result of industry evaluations modifying their specifications. An adequately stabilized controller is critical to maximizing the industry's production rate. In this study, PID controller parameters Kp, Ki, and Kd (Gain coefficients of P (Proportional), I (Integral) and D (Derivative) controller) have been stabilized by using the Particle Swarm Optimization method followed by which performance indices have been calculated to observe the error rate on the calculated Kp, Ki, and Kd values. Compared with typical PID tuning approaches, particle swarm optimization tuning for controller parameters improves process properties such as time-domain requirement, supply interruptions, error reductions, and enhanced system reaction time. MATLAB/Simulink was used to run the simulations. [ABSTRACT FROM AUTHOR]

To address the presence of network-induced delays in networked control systems (NCSs), a dual event-triggered mechanism (DETM) is used to investigate the problem of reducing network delays and controller co-design. Firstly, the DETM of the sensor–controller (SC) and the controller–actuator (CA) is adopted. By determining whether the sampled data meet the event-triggered threshold conditions for network transmission, we effectively reduce the sampled data transmitted over the network, which can reduce a network delay by reducing occupation of the network resources. Secondly, a dual event-triggered NCS model with a network-induced delay is developed, and a Lyapunov function including a DETM and network-induced delay is chosen. The functional upper limit of the Lyapunov function is estimated by combining the Wirtinger's-based integral inequality with the reciprocally convex approach. This results in a stability criterion for systems with low conservativeness and a controller co-design method for a DETM. Finally, the availability of this method was verified through a numerical example and case study. [ABSTRACT FROM AUTHOR]

This paper proposes a co-design method of dynamic output feedback control law and periodic event-triggered control (PETC) strategy to tolerate a maximum allowable number of successive packet dropouts (MANSDs) in networked control systems (NCSs). For the purpose of striking a balance between saving limited communication resources and reducing complexity of the transmission implementation, we present the periodic event-triggering mechanism (PETM), in which the triggering conditions only needs to be monitored at each event-verifying instant. In NCSs, packets often suffer from some interference in network transmission, such as packet losses. For packet dropouts, we introduce a dropout variable and model the whole closed-loop systems as a hybrid system. Furthermore, some stability conditions for co-design are given by a novel Lyapunov function and stability theorems of hybrid systems, and the explicit designs parameters of controller and triggering conditions are presented to ensure L 2 stability. Finally, two illustrated examples are given to show the effectiveness of the proposed design methods. • A co-design method of PETM and control law is proposed to save network resource. • The method aims at achieving desired stability properties while tolerating a MANSD. • The method provides less conservation results than the emulation-based approach. • The overall system is modeled based on the hybrid system framework. • By using a modified Young's inequality, rigorous stability analysis is provided. [ABSTRACT FROM AUTHOR]

This paper is concerned with the stochastic model predictive control problem (SMPC) for a class of networked control systems with exogenous disturbances and restrictions on communication frequency. A self-triggered SMPC algorithm with an improved triggering condition is designed which integrates the co-design of both the current control inputs and the maximum sampling interval, with the aim of reducing the amounts of communication transmission while guaranteeing the specific performance. To give consideration to both probabilistic guarantee and computability, chance constraints on both states and inputs are transformed into deterministic ones by leveraging Cantelli's inequality and linearisation techniques, so as to be solvable for the optimisation problem. Meanwhile, the nonconvex terms in dynamics of covariance propagation are averted through introducing the covariance upper bound control approach. The formulated online optimisation problem is convex to all decision variables. The theoretical analysis on recursive feasibility and closed-loop stability is addressed for the proposed self-triggered SMPC scheme. Finally, the efficacy and achievable performance of the proposed algorithm are showcased through numerical simulations. [ABSTRACT FROM AUTHOR]

In recent years, in-vehicle networks are increasingly being incorporated to self-driving cars in order to interconnect spatially distributed devices such as sensors, actuators, and controllers, leading to networked control systems (NCS). The main aim of this work is to reduce the use of resources in a NCS (bandwidth, device batteries) while maintaining an accurate path following for a self-driving car. Some typical network-induced drawbacks such as time-varying delays, packet dropouts and packet disorder will also be coped with. In order to reach the goals, a systematic integration of periodic event-triggered sampling techniques, packet-based control strategies, and state estimation methods is proposed. A novel non-uniform dual-rate extended Kalman filter (NUDREKF) is formulated to estimate the system state at fast, control rate from scarce slow-rate measurements. Due to its mathematical simplicity and low computational cost, the dynamic control law is designed from an inverse kinematic bicycle model and a proportional feedforward controller. Interestingly, optimal parameters for the event-triggered conditions are reached, leading to a satisfactory trade-off between resource savings and control performance. Simulation results for a real trajectory considering actual limitations for the actuators reveal the benefits of the control proposal compared to a conventional control approach.

Summary: A scheduling strategy of variable sampling period combined with deadband feedback for networked control system is proposed. Variable sampling period algorithm can allocate a reasonable sampling period to each controlled loop according to the network utilization and packet transmission time. Deadband feedback algorithm can alleviate network congestion by appropriately adjusting the packets in the network when the networked control system cannot be scheduled. According to the actual overload and utilization of the network, the designed scheduling strategy dynamically adjusts the sampling period and priority, and improves the performance of the system combined with deadband feedback. Based on the TrueTime platform, the proposed scheduling strategy is verified on a three controlled loops networked control system with interference nodes and limited network resources. The simulation results demonstrate that the designed scheduling strategy can overcome the uncertainty of the upper bound of network resources, improve output control performance, reduce integral absolute error value of the controlled loop, and shorten the packet transmission time. The overall control performance of the system is improved. The designed scheduling strategy is effective. [ABSTRACT FROM AUTHOR]

In this paper, the design of a dynamic output feedback controller for a networked control system with dual-channel data packet loss and special discrete-time delay is studied, in which the data packet loss is described by the Markov process. In order to effectively alleviate the problem of network congestion, a quantizer was added to the sensor-to-controller channel. The transition probabilities of the Markov process are uncertain, but they exist in the convex sets of known convex polyhedron types. The mode-dependent Lyapunov function was constructed, and a sufficient condition was given to make the closed-loop system stochastically stable and satisfy the performance index. The parameters of the controller were solved by the linear matrix inequality method. Finally, an example of aircraft shows the validity of the proposed approach. A numerical example is compared with other literature, showing the superiority of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, the fault detection problem of a networked control system (NCS) is studied in a cloud environment. Packet dropout and time delay in the wireless network are considered, which they are modelled as a time-homogeneous Markov process. Besides the network problems mentioned previously, an abrupt fault has been applied to the system actuator. Based on this, a fault detection filter is constructed. Sufficient conditions are given in the form of linear matrix inequality (LMI). The obtained LMI has more advantages than others existing in the literature which make the filter detects the fault in less time. Finally, a comparative study is provided to show the efficiency of the proposed approach. Also, the approach has been applied to a DC motor to validate the results. [ABSTRACT FROM AUTHOR]

Summary: This paper is concerned with the distributed secure balancing control problem for battery energy storage systems (BESSs) in a Direct Current (DC) microgrid. The Denial‐of‐service (DoS) attacks, which appear in a random way, are taken into account during the data exchange of individual BESS units. By introducing a well‐designed compensation term, an improved distributed consensus algorithm is developed to deal with the state‐of‐charge (SOC) balance issue in the presence of randomly occurring cyber attacks. With the aid of the Lyapunov stability theory, sufficient conditions are established for the networked control system such that the balance of the SOC for each BESS unit is achieved under certain constraints. The effectiveness of the proposed balance scheme is verified by a series of illustrative simulation experiments. [ABSTRACT FROM AUTHOR]

This paper deals with the design problem of multiloop networked control system (NCS) under interchange attack. This is a new type of attack where the transmitted data are swapped between different control loops which can be more destructive than other types of attacks, such as denial‐of‐service (DoS) attack. In this context, multiple sampled‐data control loops are first considered that use a shared communication network for data transmission. Then, the overall closed‐loop systems with the proposed attack are formulated in a unified stochastic delay system. The proposed framework is also applicable to DoS attack. Based on Lyapunov–Krasovskii theory and stochastic analysis techniques, some conditions in terms of linear matrix inequalities (LMIs) are derived for the H∞$$ {\mathcal{H}}_{\infty } $$ control design problem. Finally, two inverted pendula are utilized for simulation to show the effectiveness of the proposed method. Also, the effects of DoS attack and interchange attack are compared. [ABSTRACT FROM AUTHOR]

Oil and gas projects differ from regular investment projects in that they are frequently large-scale, categorised as vital national projects, highly technological, and associated with significant risks. Drilling rigs are a crucial component of the oil and gas sector and the majority of the systems and equipment aboard drilling rigs are operated automatically. Consequently, it is crucial to address the topic of an advanced control theory for off-shore systems. Network technology connected to control is progressively being used to replace outdated technologies, together with other contemporary technologies. In this study, we examine how to adapt a networked control jacking system to the effects of internal and external disturbances with a time delay, using a Fuzzy controller (FC)-based particle swarm optimisation. To demonstrate the benefit of the proposed approach, the developed Fuzzy Particle Swarm Optimisation (FPSO) controller is compared with the fuzzy controller. Finally, the results from simulations and experiments utilising Matlab software and embedded systems demonstrate the suitability of the proposed approach.

This paper focuses on network time delay, network congestion, and network security in the networked control system. A secure event-based quantized networked control system (SEQNCS) is proposed to address these problems. The predictive method in the SEQNCS actively compensates time delay both in the forward channel and feedback channel according to the previous states and control inputs. Both the event-driven strategy and quantizer are introduced into the SEQNCS to alleviate network congestion by the event trigger conditions and quantization density. The encrypted encoding quantizer is constructed in the SEQNCS to implement the protection of data security under deception attacks while quantifying the transmitted data. The proposed SEQNCS achieves desired system performance of the networked control system under time delay and deception attacks while alleviating network congestion. The stability of the SEQNCS is proved by the piecewise linear model approach. Practical experiments are implemented to demonstrate the effectiveness of the proposed SEQNCS. [ABSTRACT FROM AUTHOR]

Summary: This paper studies the networked control systems (NCS) predictive output feedback control issue with random time delay and denial of service (DoS) attacks. The mathematical description of the random DoS attacks and time delays in controller‐to‐actuator (C‐A) and sensor‐to‐controller (S‐C) communication channels is researched based on Markov stochastic theory. Considering the random characteristics of network‐induced attacks and delays, the closed‐loop NCS is modeled as a discrete‐time linear system with Markov DoS attack and time delay. The stochastic stability criterion of a class of networked predictive control systems with random attack and delay is proposed based on Lyapunov stability theory and the predictive compensation control method. The networked model predictive output feedback controller is designed by applying the parameter compensation method and linear matrix inequality (LMI) technique. Numerical simulation results are proposed to verify the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This study investigates the problem of finite-time contractive stability analysis and observer-based H ∞ fault-tolerant control (FTC) for linear network-based control systems subject to network-induced time-varying delay. It is assumed that the faults occur in the both actuator and sensor components. For the sake of data transmission reduction, an aperiodic-sampling-based adaptive event-triggered scheme is used, in which the interval between two sampling instants varies within a certain known bound, and the event threshold is adjusted by using the adaptive rule. An unknown input observer (UIO) is used to estimate the system states and faults simultaneously. Then, using Lyapunov–Krasovskii stability theory, delay-dependent sufficient conditions for the observer-based FTC of the networked control system (NCS) are derived. These conditions are presented in the form of linear matrix inequalities (LMIs), ensuring that both the error system and the closed-loop NCS achieve finite-time contractive stability while simultaneously satisfying the H ∞ performance index. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed design approach. [ABSTRACT FROM AUTHOR]

In actual operation, there are security risks to the data of the network control system, mainly in the form of possible eavesdropping of signals in the transmission channel and parameters in the controller leading to data leakage. In this paper, we propose a scheme for encrypting linear controllers using fully homomorphic encryption, which effectively removes these security risks and substantially improves the security of networked control systems. Meanwhile, this paper uses precomputation to handle data encryption, which eliminates the encryption time and solves the drawback of fully homomorphic encryption that it is difficult to apply due to the efficiency problem. Compared to previous schemes with precomputation, for the first time, we propose two methods to mitigate the problem of the slight security degradation caused by precomputation, which makes our scheme more secure. Finally, we provide numerical simulation results to support our scheme, and the data show that the encrypted controller achieves normal control and improves safety and efficiency.

Abstract This study researches the H ∞ control issue for a networked Markovian jump system with data packet loss occurring not only in the channel from sensor to controller but also in the channel from controller to actuator via an observer. The mathematical model for the closed‐loop networked Markovian jump system with data packet loss is established. The necessary and sufficient conditions for the closed‐loop system to be stochastically stable are derived. The design approach of the controller and the minimal performance index of the external disturbance suppression are also given in the case that the transition possibilities of the system modes and the data packet loss are both partially unavailable. Finally, two numerical examples are used to illustrate the effectiveness of the proposed method.

This paper presents a novel event-triggered predictive control (ETPC) approach for the stabilization of discrete-time output-feedback networked control systems (NCSs). The studied NCS is considered to be subject to both random external input and output disturbances, and network imperfections including random communication delay, random packet dropout, packet disorder, limitation of network bandwidth, and network resources. In the proposed algorithm, an observer-based event detector is designed for reducing the number of sent packets through the communication network using the estimated system states by the Luenberger observer. In this way, the system’s energy resources are saved and network-induced effects are skipped. A switched predictive controller with multiple gains are used to compensate for network-induced effects. Controller gains are designed compatible with different possible values of delays and packet dropouts. A novel augmented representation of the state-space equations of the system is derived to design observer gain and controller gains. The asymptotic stability of the system is guaranteed by designing the observer and controller based on the Lyapunov function through solving linear matrix inequalities (LMIs). Putting all the aforementioned points together has made the whole framework presented in this paper a comprehensive one. The effectiveness of the proposed approach is demonstrated by comparative simulation results.

This paper studies the controller design of sampled data robust adaptive control (RAC) with control update strategy for a class of networked uncertain nonlinear systems under random denial-of-service (DoS) attacks with frequency and duration constraints. Two switching-type robust adaptive controllers with corresponding update strategies based on certain triggering conditions are proposed to stabilize the uncertain nonlinear system with known and unknown control coefficient, respectively. The uniform ultimate boundedness (UUB) of the solutions of the closed-loop systems under DoS attacks is guaranteed. Finally, the effectiveness of the proposed control law is verified by an example with numerical simulation. [ABSTRACT FROM AUTHOR]

This paper presents a state feedback control design with an event-triggered scheme for the Maglev Train (MagT.) system with a saturated control input. In a state feedback control design that precisely tracks the position of the coil current and coil voltage of actuated levitation system, we first derived the mathematical model in the form of a state–space model from the MagT. model; then, we implemented the saturated control input to encounter the uncertainties. A new event-triggered mechanism, in which the threshold parameter remains constant with resulting states, is utilized to save the constrained network resources and improve information exchange efficiency. Using the Lyapunov–Krasovskii functional method, a defensive control is established in the form of linear matrix inequalities (LMIs) for the resultant system. Finally, it is shown through the most practical approach example that the proposed method in this paper is effective for ensuring better system performance. [ABSTRACT FROM AUTHOR]