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A networked output feedback loop subject to packetized transmissions of the output signal is considered. Based on the small gain theorem, an easy‐to‐use stability criterion covering two important cases is presented. In the first case a packet numbering mechanism is employed whereas in the second case neither packet numbering nor synchronization between sender and receiver is assumed. The analysis makes use of acausal subsystems and deduces the optimal constant time delay with respect to the minimization of the ℓ2 gain due to uncertain packet delays. This additional delay is then used in a nominal controller design such that additional admissible packet delay variations introduced by the network are maximized. A simulation example of a networked control system with a filtered Smith predictor illustrates the application of the proposed criterion. It is shown that the proposed novel technique is less‐conservative than existing stability criteria based on the small gain theorem.

In this study, a sampled-data networked control system over a multipath routing-enabled network is investigated, where each delivered signal in a path suffers a random delay. For such a system, the mean square stabilisation problem is considered under the joint design of the event-driven strategy on the actuator side and the control policy on the decision-maker side. The contributions of this study are twofold. First, by pre-defining an application time as an event-triggering parameter, the sampled-data system is transformed into a stochastic form with input delay and packet dropout. When the probability distribution F ( ⋅ ) of random delay is known a priori, the close form of packet dropout rate is proposed and a set of necessary and sufficient stabilisation conditions are developed simultaneously. When F ( ⋅ ) is unknown, the reduced system is an uncertain dynamic system. Utilising matrix polynomials, a verifiable criterion is derived for stabilising the uncertain system, which is also necessary and sufficient. Second, for the scalar system, the close form of allowable sampling period bound is developed in terms of F ( ⋅ ) and system parameters.

In this study, the observer-based output feedback H ∞ control problem is investigated for the two-dimensional (2D) networked control system (NCS) in form of Fornasini–Marchesini second model. The communication from the controller to the actuator is carried out through a shared network medium, where only one signal gets the network access at each transmission instant. To avoid data collisions, the periodic scheduling protocol is employed to assign the network access priority to the actuator in chronological order. To improve the reliability of data transmission, redundant channels are applied to deliver the measurement observed by the sensor to the controller. The aim of the addressed problem is to design an observer-based output feedback controller so that the considered 2D NCS satisfy a predefined H ∞ performance index. Sufficient condition is given to ensure the H ∞ performance of the closed-loop system via the Lyapunov theory and stochastic analysis. Moreover, the observer-based output feedback controller is designed to achieve the desired H ∞ performance index, under which the controller parameters are determined by solving certain optimisation problems. Finally, a numerical example is given to demonstrate the feasibility of the proposed approach.

This study addresses an observer-based model predictive control (MPC) algorithm for a networked control system (NCS) under denial of service (DoS) attacks and actuator saturation via an interval type-2 Takagi–Sugeno (IT2 T–S) fuzzy model. With few studies undertaking the cyber security problems in the research of MPC algorithm, this study considers the data transmission problem when DoS attacks occur. Under DoS attacks, signals in the communication networks will be interfered. The probability of error-free packet reception depends on signal-to-interference-plus-noise ratio of the wireless transmission networks. In order to reduce the on-line computation, an off-line fuzzy observer is devised to estimate the system states. Meanwhile, an on-line MPC algorithm is proposed to minimise the performance objective function and obtain the secure model predictive controller gain. Besides, the recursive feasibility is ensured by refreshing the bound of estimation error. Finally, illustrative examples certificate the effectiveness of the presented method.

This study is concerned with the output-based resilient event-triggered control for networked control systems (NCSs) subject to denial of service (DoS) attacks, where 'resilient' is interpreted as that the NCSs can tolerate a larger time delay with a certain degree of performance degradation when there are DoS attacks. Otherwise, the NCSs run with $H-{\infty }$H∞ performance. In order to characterise DoS attacks, an additional positive term which implies the effects of DoS attacks is imposed on the pre-designed triggering condition. By considering the fact that only partial output measurements can be obtained, the output-based security performance analysis as well as an output feedback controller design under the proposed event-triggered strategy is conducted with Lyapunov-Krasovskii method and linear matrix inequalities technique. At last, the simulation results show that the designed controller is resilient to DoS attacks with less dependent on the transmission packets while sacrificing some control performance.

This study addresses the sliding mode controller design for a networked control system with quantisation and random packet loss. A logarithmic quantiser is adopted in order to guarantee the coarsest density and decrease the possibility of unsuccessful transmission. The quantisation process is designed as an event driven to reduce the amount of data to be transmitted over the channel. A sliding mode controller is adopted to suppress the measurement noise and error caused by the features of a wireless communication channel. The existence of quasi-sliding mode in the sense of mean-square and closed loop stability in the sense of mean square are claimed. Simulations are carried out to support the algorithms proposed.

This study addresses mean-square stability of networked control system with state quantisation process and suffers random packet losses. A logarithmic quantiser is applied in order to decrease the possibility of the packet loss phenomenon. Also, the quantisation process is designed as event driven so that the quantisation is only performed when necessary. It is shown that stability in mean-square sense is achieved if a series of LMI conditions are valid. Simulations are finally performed to show the effectiveness of the results of the theoretical analysis.

In this paper, a cooperative distributed model predictive control is proposed for a class of large-scale systems composed of discrete-time linear subsystems which are coupled via states. The subsystems communicate with each other through a network with communication delays and they do not have direct access to their local states. In the proposed scheme, each subsystem is associated with a local MPC unit, a local predictor and a local observer. The local model predictive controllers exchange predicted input sequences via a delayed communication network. The local predictor uses the explicit model of the subsystems and predicts those states which are coupled between subsystems and their actual values are not available due to delays. The states of each subsystem are estimated from local measurements by designing a local observer. Convergence analysis of the proposed estimation methodology is performed and it is shown that the observer and predictor have exponential convergence. Furthermore, the exponential stability of the closed-loop system is existed. Finally, the theoretical results are verified by a simulation study.

This study investigates sliding mode control (SMC) for non-linear networked control systems (NCSs) subject to packet disordering as well as external disturbances. The main objectives of the proposed method are to predict packet disordering and to stabilise the NCSs in case of the unknown packet disordering in the future. Firstly, linearisation of non-linear systems and the technology of adopting the newest control input with a stochastic parameter are employed to model the system as a linear Markovian jumping system. Secondly, with the application of a time series prediction model, the phenomenon of disordering better under the novel measurement is portrayed. Then, robust H ∞ SMC is designed by solving the linear matrix inequalities (LMIs). Finally, examples with sampled disordering packets are simulated to illustrate the effectiveness and advantages of the proposed method.

A new systematic scheme is proposed for demand-side management and control of a class of networked smart grid. The networked smart grid is modelled into an evolutionary game, and the theory of semi-tensor product is applied to analyse its dynamic behaviours. By using a newly defined stacked form of structural matrix, a closed-loop feedback control is designed to shape the structural matrix of the evolutionary game, such that the Nash equilibrium (with respect to minimum total cost) can be reached and maintained. Based on the proposed feedback control, a robust control can be designed for the smart grid to reach the Nash equilibrium in case of model uncertainties resulted from fake behaviours of some users. Examples are provided to illustrate the theoretical results.

A distributed control algorithm using a new idea of collaborative processing for networked control systems with limited computational resources is proposed. In a networked control system, the processing unit is required to complete multiple tasks (such as control, sensing, signal processing, etc.) in a timely manner. Due to limited computational resources that are available to the processing unit, the assumption that the control input is computed at every time step may no longer hold. There are multiple remote controllers and each controller controls its own plant is considered. The authors give the controllers within a neighbourhood the ability to compute their neighbours' control inputs. By suitable design of the processor collaboration algorithm, their are able to ensure the stochastic stability of the entire system even if there are random computation interruptions occurring at different time steps. Numerical results verify the effectiveness of the algorithm.

This study deals with the optimal control problem for a class of delta-domain networked control systems (NCSs) subjected to both matched and unmatched disturbances. In the presence of the disturbances, the so-called ϵ -optimum is proposed to quantify the control performance. The purpose of the addressed problem is to design the optimal control strategy such that the cost function is minimised over the finite-/infinite-horizon under the network-induced constraints. In virtue of the dynamic programming method, sufficient conditions are established to guarantee the existence of the desired control strategies, and the controller parameters are designed. For the obtained optimal control strategy, an upper bound for the ϵ -optimum is provided explicitly, and convex optimisation algorithms are given to compute such upper bound. Both simulation and experimental results are provided to illustrate the usefulness and applicability of the proposed methods.

This study is concerned with the output-feedback control problem for a class of stochastic high-order non-linear systems with time-varying delays. A distinctive feature of the control scheme is that the restrictions on delay-dependent drift and diffusion terms are greatly relaxed by using radial basis function neural network (NN) approximation approach. Furthermore, with the approach, the specific knowledge of NN nodes and weights is not required. Under some weaker conditions, by combining dynamic surface control technique with proper Lyapunov–Krasovskii functional, an adaptive NN output-feedback controller is designed constructively such that the closed-loop system is 4-moment (or mean square) semi-globally uniformly ultimately bounded. Finally, the control scheme is applied to both a practical stochastic robot system and a numerical system to demonstrate the effectiveness of the proposed approach.

This study is concerned with adaptive model-based event-triggered control of an uncertain continuous system with external disturbance. The proposed framework incorporates two important control techniques for reducing communication burden and regulating the states of the system online in control network, that is, adaptive model-based networked control system and event-triggered control (ETC). An adaptive model of the plant is capable of generalising the zero-order hold implementation in traditional ETC schemes, while also providing stability thresholds that are robust to model uncertainties. In the adaptive model-based controller, the authors present an update law to estimate the parameters of the adaptive model at triggered instant. After revisiting the adaptive model property in the context of event-triggered communication, an event-triggered condition is proposed using the Lyapunov technique. The stability condition of the proposed approach does not need explicit knowledge of the plant parameters, but are given only in terms of the parameters of the adaptive model and some bounds in the model uncertainties. In addition, lower bound on transmission periods are provided. Meanwhile, L 2 stability with respect to external disturbance is examined. A real-time simulation example is presented to demonstrate the effectiveness of the theoretical results.

This study investigates controller design for networked control systems under hybrid driven scheme. A hybrid driven communication scheme is proposed, which can improve the system performance and reduce the network transmission. A Bernoulli distributed stochastic variable is introduced to describe the switch law of the communication scheme. A general system model under hybrid driven scheme is then constructed. Based on this model, sufficient conditions are derived to guarantee the desired system performance. Furthermore, criteria for co-designing both the feedback gain and the trigger parameters are established. Finally, simulation results show the usefulness of the proposed method.

This study proposes a novel sampling and control strategy to find a suboptimal sampling period sequence and control input sequence, such that a quadratic cost function of state and control input of a networked control system (NCS) with packet disordering is minimised. First, a discrete-time system model of the NCS with packet disordering, transmission delay and packet loss in terms of displacement values of packets is put forward. Second, a linear quadratic regulation (LQR) problem of the NCS is formulated, showing that the optimal controller depends on sampling period and quality of services (QoS) of networks. Interactive effects between sampling period and QoS of networks pose a challenge in solving the LQR problem of the NCS. To overcome this difficulty, different from traditional transmission-delay-based or packet-loss-based sampling scheme, a novel packet-disordering-based sampling period selection scheme is proposed. Furthermore, an algorithm is presented to find a suboptimal solution to the LQR problem in this study. Finally, simulation results demonstrate the effectiveness of the proposed approach.

This study is concerned with the control problem of networked non-linear systems with communication delay and data dropout. A networked non-linear predictive control scheme is proposed to compensate for communication delay and data dropout actively rather than passively. The stability analysis shows that the stability problem of the closed-loop networked non-linear predictive control system is converted to the one of a conventional non-linear control system without network. The simulations illustrate that the proposed scheme can compensate for communication delay and data dropout, and achieve the same control performance of the local closed-loop control system without network.

This study investigates the problem of event-triggered output-feedback ℋ∞ control for networked control systems (NCSs) with non-uniform sampling. First, an event-triggered communication scheme is proposed, in which the output of the system is taken sample with a non-uniform sampling period, while whether or not the sampled data should be transmitted is determined by a predetermined well-designed event-triggering condition. Second, the event-triggered NCSs are modelled as a time-delay system, which regards the measured output-error between the output at the current sampling instant and the output at the last transmitted sampling instant. As a result, the stability and synthesis criteria are derived to guarantee the uniform ultimate bounded stability and the desired performance while using the less communication bandwidth. Finally, three illustrative examples are used to show the effectiveness of the proposed method.

This study is concerned with the data-based control of networked non-linear control systems with random packet dropouts in both the sensor-to-controller and controller-to-actuator channels. By taking advantage of the characteristics of networked control systems such as the packet-based transmission, timestamp technique, as well as smart sensor and actuator, a data-based networked predictive control (DBNPC) method is proposed to actively compensate for the two-channel packet dropouts, where only the input and output data of the non-linear plant are required. A sufficient condition for the stability of the closed-loop system is developed. Furthermore, the resulting DBNPC system can achieve a zero steady-state output tracking error for step commands. Finally, extensive simulation results on a networked non-linear system demonstrate the effectiveness of the proposed method.

In this study, the design of the optimal decentralised full-state-feedback controllers is derived for wireless networked control systems with network-induced delays. In particular, the authors formulate the optimal decentralised control problem as a non-cooperative linear quadratic game. Then, the optimal control strategy of each controller is obtained that is based on the current plant state and the last control strategies of decentralised controllers. The proposed optimal decentralised controllers reduce to the known controller under certain conditions. Moreover, the authors illustrate the application of the proposed decentralised state feedback control to load frequency control in power grid systems.

In this study, the authors develop a data and event-driven control scheme that combines data and event-driven control methods, for a class of networked non-linear control systems, which consist of a remote controller and a local non-linear control system. The plant in the local non-linear control system has an unknown dynamic model. They apply a data-based method to design and adjust the feedback gain matrix for the plant, whose desired outputs are given by the remote controller. This method has advantages of both data and event-driven control methods. Moreover, the proposed scheme provides an alternative option to realise remote control, when the dynamic model of the plant is unknown. They then present theoretical analysis on the convergence condition and a computer simulation example to demonstrate the feasibility of the developed control scheme.

This study is concerned with the problem of controller design for linear systems with unknown or partially known communication delay. A new networked predictive control scheme is proposed to deal with the unknown or partially known communication delay. The closed-loop system is modelled as a switched system under constraint switching taking an important property of communication delay into account. Sufficient stability conditions are derived using switched Lyapunov function approach. On the basis of stability conditions, the method of designing the controller gain matrix and some important parameters in the control scheme is investigated. Finally, a numerical example is given to confirm the effectiveness of the proposed method.

In a distributed ‘networked control system’ (NCS), multiple physical systems or agents are connected to their corresponding controllers through a shared packet-switched communication network. For such distributed NCS, periodic sampled controller design is unsuitable to handle packet-switched closed-loop control systems and a novel stochastic optimal adaptive event-sampled controller scheme is proposed in the application layer for each physical system or agent expressed as an uncertain linear dynamic system. Lyapunov stability analysis will be utilised to derive the event trigger condition. In addition, a network scheduling protocol is also required for such NCS. Traditional network scheduling protocols are unsuitable for such NCS since the behaviour of the physical systems is disregarded during the protocol design. Therefore in this study, a novel distributed network scheduling protocol via cross-layer approach is developed to improve the performance of distributed NCS by minimising an overall system cost function which consists of the information collected from both the event-triggered controller for each physical system in the application layer and the distributed scheduling protocol from the network layer. It will be demonstrated that the proposed co-design approach will not only allocate the network resources efficiently but also it will improve the performance of the overall distributed NCS. Simulation results are included to demonstrate the effectiveness of the proposed cross-layer co-design.

This study studies the problems of stability analysis and stabilisation for networked control systems. The networked control system is modelled as a Markovian jump time-delay system, which is transformed into an interconnected form by the transformation approach. Then, the new stability and the stabilisation conditions are presented based on the scaled small gain theorem and the Lyapunov functional method. The results are much less conservative than other existing results because of the utilisation of the input–output method and some novel techniques. In the illustrated example, the controller of mechanical networked control systems is obtained by the stabilisation condition, which illustrates the less conservatism and effectiveness of the authors’ method.

This study is concerned with modelling and observer-based H ∞ controller design for a continuous-time networked control system with network-induced delays and packet dropouts. A new model for an observer-based networked control system is first established by proposing a linear estimation-based delay compensation method. Then some controller design criteria are obtained by constructing an interval time-varying delay decomposition-based Lyapunov functional. A new bounding inequality is introduced to transfer non-linear matrix inequalities into a solvable optimisation problem. A numerical example is given to illustrate the merits and effectiveness of the obtained results.

The problem of H ∞ fault-tolerant control for networked control systems (NCSs) with actuator failures is addressed in this study. The authors consider the network-induced delays, including sensor-to-controller delay and controller-to-actuator delay, to have both an upper bound and a non-zero lower bound. By using a sampled-data approach, a new model is formulated based on the updating instants of the ZOH. They derive the criteria which ensure that the sample-data NCS is stable with H ∞ norm γ. The authors design the H ∞ fault-tolerant controller that guarantees the closed-loop NCS stability with H ∞ norm γ, when all control components are operational, as well as when some actuators fail to operate. Simulation examples are given to show the effectiveness and less conservative needs of the proposed method.

This study is concerned with the event-triggered control for networked control systems via dynamic output feedback controllers (DOFCs). The output measurement signals of the physical plant are sampled periodically. An output-based discrete event-triggering mechanism is introduced to choose those only necessary sampled-data packets to be transmitted through a communication network for controller design. Under this event-triggering mechanism, the resultant closed-loop system is first modelled as a linear system with an interval time-varying delay. Then a novel stability criterion is established by employing the Lyapunov-Krasovskii functional approach. Based on this stability criterion, a new sufficient condition is derived to co-design both the desired DOFCs and the event-triggering parameters. Finally, a satellite control system is taken to show the effectiveness of the proposed method.

This study deals with the problem of reliable precise tracking control for the networked control system with non-zero external inputs (NEIs). A new control scheme is developed by introducing an integral item in the control law and taking stochastic actuator failure (SAF) into account, by which a better steady tracking performances can be achieved. Based on Lyapunov theory, a reliable control design method that guarantees the network-based tracking control systems with zero steady-state error in the conditions of both NEIs and SAFs is designed. Simulation results demonstrate the effectiveness of the developed controller design scheme.

This study investigates the finite-time cooperative-tracking problem for a class of networked Euler-Lagrange systems with a leader-follower structure, where the leader has an active dynamics and only a subset of the followers have access to the leader system. A novel framework for the design of finite-time cooperative-tracking controller is proposed by using sliding-mode control theory and graph theory. First, a finite-time sliding-mode tracking protocol is proposed for the networked Lagrange systems in the presence of bounded model uncertainties and external disturbances. Under the condition that the bounds of the model uncertainties and external disturbances are unknown, adaptive finite-time cooperative-tracking protocol is then presented. The finite convergence time is also estimated. Finally, we analyse the tracking performance of the networked uncertain Lagrange systems under the action of a continuous control protocol, which guarantees that the tracking errors converge to an arbitrarily small bound around zero in finite time. Simulation examples are presented to show the effectiveness of the obtained theoretical results.

This study presents distributed event-based control strategies for a networked dynamical system consisting of N linear time-invariant interconnected subsystems. Each subsystem broadcasts its state over the network according to certain triggering rules that only depend on local information. The system can converge asymptotically to the equilibrium point under the proposed control design, and the existence of a lower bound for the broadcasting period is guaranteed. A novel model-based approach is derived to reduce the communication between the agents. Simulation results show the effectiveness of the proposed approaches and illustrate the theoretical results.

This study deals with a robust trajectory tracking control problem of discrete-time networked control systems. The systems have time-varying interval-bounded uncertainties, random network-induced delays and data dropouts in both sensor-to-controller channel and controller-to-buffer/actuator channel. A dynamic predictive feedback linearisation controller is proposed so that the system dynamics and delays caused by networked communication time and data dropouts are compensated, and the system output can perfectly track the reference trajectory when uncertainties are absent. Tracking errors caused by the time-varying parameter uncertainties are suppressed in the H ∞ sense. Finally, the proposed method is illustrated by two numerical examples which show the application procedure and effectiveness of the proposed control scheme.

In many applications, add-on type repetitive controllers have been reported to have prominent capability of attenuating periodic disturbances and/or tracking periodic reference commands. However, the effective information such as performance weighting functions for the design of feedback controllers has not been considered sufficiently on the design of repetitive controllers. In this study, we deal with a problem of a robust repetitive controller design for an uncertain feedback control system using its explicit performance information. We first show that a robust stability condition of repetitive control systems has a similar form with the well-known robust performance condition of general feedback control systems. The repetitive controller is designed using the performance weighting function for the design of the robust feedback controller. It is also shown that a steady-state tracking error of the repetitive control system is described in a simple form without time-delay term. This result yields that the repetitive control system has a much larger loop gain in the steady state than the feedback control system. Moreover, this paper provides sufficient conditions ensuring that the power of the steady-state tracking error in the repetitive control system is less than or equal to that of the feedback control system. Based on the obtained results, we present repetitive controller design method using the design information of the feedback control system. Finally, application studies on the track-following control system of optical disk drives are performed to show the validity of the proposed method.

This study presents the design of an adaptive Kalman filter for networked systems involving random ‘sensor delays, missing measurements and packet dropouts’. Two different adaptive filters are considered to estimate unknown parameter vector associated with the system matrices and subsequently the estimation of state and parameters of the system based on the minimisation of square of the output prediction error is adopted in bootstrap manner. An estimator-based robust controller design has been proposed for asymptotic stability of the system whose parameters can vary within a known bound. The effectiveness of the designed algorithms is tested through a numerical example under different cases.

In this study, a collection of agents performing a shared task making use of relative information communicated over an information network is considered. A two-step control design procedure for distributed control of such systems is proposed. The control law is guaranteed to provide a certain level of H2 performance at a network level. An analysis of the proposed control law in the presence of delays in the relative information is carried out to obtain a bound on the maximum delay possible.

A control structure is investigated where the sensor is remotely located from the plant through the communication network, motivated by the inclusion of sensor fusion in networked control systems (NSCs). This control structure admits a broad class of practical NSCs but has rarely been touched before. Motivated by the packet-based control approach, the authors propose an offline model predictive control-based gain scheduling scheme for this control structure. This scheme is capable of actively compensating for the communication constraints, which is an impossible task for conventional control approaches, and at the same time it dramatically reduces the communication and computational costs compared with the packet-based control approach. In this sense, this scheme can be regarded as an important step towards the effective convergence of control, communication and computation.

In this study, an improved observer-based stabilising controller has been designed for networked systems involving both random measurement and actuation delays and subject to non-stationary packet dropouts. The developed control algorithm is suitable for networked systems with any type of delays. By the simultaneous presence of binary random delays and making full use of the delay information in the measurement model and controller design, new and less conservative stabilisation conditions for networked control systems are derived. The criterion is formulated in terms of linear matrix inequalities. Detailed simulation studies on representative systems are provided to show the applicability of the developed design technique.

In this study, a single neural network (SNN)-based adaptive control design method is developed for a class of uncertain non-affine pure-feedback non-linear systems. Different from existing methods, all unknown parts at intermediate steps are passed down, and only an SNN is used to approximate the lumped unknown function of the system at the last step of controller design. By this approach, the designed controller consisting of an actual control law and an adaptive law can be given directly, and the complexity growing problem inherent in conventional methods can be completely eliminated. Stability analysis shows that all the closed-loop system signals are uniformly ultimately bounded, and the steady-state tracking error can be made arbitrarily small by appropriately choosing control parameters. Simulation results demonstrate the effectiveness of the proposed approach.

This study presents a co-design strategy for networked control systems (NCS) that is effective for treacherous Internet conditions. The co-design is based on two adaptation layers, one on each side of the network, that make the scheme controller-independent. Two different designs based on anticipative control are presented for packet-based NCS. In the first (which is time-based), the controller works asynchronously, but the sensor sends the plant state periodically. The second design is event-based, as the sensor only sends packets when a certain condition is met. Stability results were derived for the time-based approach, and simulation and experimental results demonstrate the efficiency of the proposed design for very long delays and high packet-loss rates. In addition, the event-based approach showed a considerable reduction in network usage.

Packet losses are a general problem in networked control system and wireless sensor networks (WSNs). In order to increase estimation accuracy and reliability, a filter with finite packet losses called minimum variance filter (MVF) is designed for stochastic systems. The authors develop a packet loss model, and design a novel MVF based on the orthogonal analysis approach. The proposed filters rely only on the packet arrival probability at each time instant and do not need to know whether the measurement is received at a particular time instant. However, the proposed MVF is not applicable to non-linear cases. So an extended MVF is derived for stochastic non-linear systems and applied to track a moving target in WSNs. Simulation results show that, compared to existing methods, the proposed MVFs have superior performance.

The authors investigate a class of observer-based discrete-time networked control systems (NCSs) with multiple-packet transmission where random packet dropouts occur independently in both the sensor-to-controller (S/C) and controller-to-actuator (C/A) channels. The authors first propose and prove the separation principle for the NCSs where packet dropouts in the C/A and S/C channels are governed by two independent Markov chains, respectively. Secondly, the authors derive a sufficient condition, in terms of linear matrix inequalities (LMIs), for stabilisation control of the Markov chain-driven NCSs. The authors also derive the necessary and sufficient condition for stabilisation control of the memoryless process-driven NCSs as a special case. A numerical example is provided to illustrate the effectiveness of our method.

In this paper, an approach to design state-feedback gain is proposed for a class of relay control systems. The resulting controller can drive states of the systems to desired limit cycles. The design consists of two steps. First, the form of the state-feedback gain is proposed. It is proved that each gain in the proposed form can guarantee the existence and stability of a limit cycle. Then, by an exact method, the value of state-feedback gain is chosen to obtain the limit cycle with prescribed characteristics. In order to demonstrate the effectiveness, the proposed approach is applied to the attitude control of a torpedo. Simulation results show that the designed relay controller drives the state of the torpedo to a limit cycle with desired amplitude and frequency.

This study addresses the stabilisation problem for a class of networked control systems (NCSs) with time delays and packet losses. Motivated by the fact that static state feedback control shows offset in the plant output when non-zero disturbance acts on NCSs, the proposed method emphasises the implementation issue and employs state feedback integral control to achieve non-zero disturbance rejection and zero steady-state error. The resulting closed-loop system is transformed into a discrete-time switched system, and the stability conditions are derived in terms of linear matrix inequalities (LMIs). The corresponding stabilising controller design technique is also developed based on the stability conditions. Simulation and experimental examples are given to illustrate the effectiveness of the obtained results.

A networked control system (NCS) is a control system where in the control loops are closed through a communication network. The distinct feature of a NCS lies in that its spatially distributed components, such as actuators,sensors and controllers/estimators, exchange data via a communication network. This offers great advantages over a conventional control system, making it possible to design a large-scale system. Thus, NCSs are of great importance in many key applications including aeronautics and astronautics, information and networks, and robot and intelligent machines, to name a few...

Fault-tolerant control of networked control systems (NCSs) with random actuator failure is studied. An innovative model is presented for this problem. It includes three sources of uncertainties, namely uncertainties in the plant model, uncertainties in networked communications and uncertainties in possible actuator failure/malfunction. Other main features are: (i) the fault statistics of each actuator is individually quantified, and (ii) a united framework is proposed to have logic zero-order-holders embedded in the NCS. The latter enables actuators - when in normal operation - to use the latest actuating signals available to them. Based on the Lyapunov-Krasovskii functional, three theorems are proved in the study for the system stability and controller design. Theorem 1 gives a matrix inequality for the system asymptotical stability in the mean-square and is the foundation of the other two theorems. Theorem 2 shows a stability condition regarding the design of a robust state-feedback control for the system under study. Finally, Theorem 3 gives a modified stability condition that can be employed for actual design. A numerical example is presented to show how such a robust controller can be designed.

When networked control systems (NCSs) are stable with any constant time delays, then they are delay-independently stable. Many works in the literature are concerned with this stability concept, giving different criterions for it. This study mainly deals with the dynamic performance of such systems and discusses the issue of 'staircase phenomenon'. The definition of 'staircase phenomenon' is given at first and it is demonstrated that existence of 'staircase phenomenon' usually means that the system's dynamic process is slow. Then it is proven that if a NCS with traditional feedback structure is delay-independently stable, then the 'staircase phenomenon' in its dynamic response cannot be eliminated. This is an inner restriction of delay-independently stable NCS under traditional feedback structures, which can only be broken by changing the system's structure. It is already proven in the literature that the introduction of scattering transformation into NCS can bring profound changes to the system's structure. This study proceeds to prove that if a NCS which is delay-independently stable is introduced with scattering transformation, then its steady-state error and 'staircase phenomenon' in its dynamic response can be eliminated altogether by tuning the parameter of the transformation. Simulation result is provided at the end.

A large number of research works on networked control systems (NCSs) are from the time delay system (TDS) perspective, however, it is noticed that the description of the network-induced delay is too general to represent the practical reality. By recognising this fact, a novel TDS model for NCSs is thus obtained by depicting the network-induced delay more specifically. Based on this model, stability (robust stability) and stabilisation results are obtained using delay-dependent analysis approach, which are less conservative compared with conventional models because of the specific description of the network-induced delay in the new model. A numerical example illustrates the effectiveness of the proposed approach.

This study is concerned with the static output-feedback stabilisation problem of discrete-time networked control systems. If the controlled plant is a discrete-time system, the networked control system with time-varying network-induced delays and data packet dropouts in the transmission is modelled as a discrete-time system with time-varying delays in the state. The network-induced delays are assumed to have both an upper bound and a lower bound. Next, an asymptotic stability condition for the networked control systems is established, which depends on the upper and lower bounds of delay times. Then, three approaches to the static output-feedback controller are proposed, where the effect of both network-induced delays and data packet dropouts has been considered. Furthermore, the robust stability condition and controller design method for such networked control systems with structured uncertainties are presented. All the results are formulated in the terms of linear matrix inequalities (LMIs), which are numerically very efficiently solved via LMI toolbox in the Matlab. Finally, three examples are worked out to illustrate the feasibility and effectiveness of the proposed method.

The modelling and stabilising control of networked control systems (NCSs) with stochastic packet loss and time-varying delays are addressed. In specific, a novel Markovian jump linear system with time-varying delays is used to model the NCS. Without using the augmented state method, sufficient conditions for the stochastic stabilisation of the NCS with packet loss and time-varying delays are obtained via the mode-dependent Lyapunov function method. The mode-dependent controller for the closed-loop NCS is presented in the linear matrix inequalities formulation via the Shur complement theory. A numerical example is given to illustrate the effectiveness of the proposed method.

This study investigates the problem of controller design for systems with uncertain sampling rates. The system is controlled through a communication network. The sampling period, within a given interval, is assumed to be time-varying and a simplified framework for the network-induced delay is considered. The overall system is thus described by an uncertain discrete-time model with time-varying parameters inside a polytope whose vertices are obtained by means of the Cayley–Hamilton theorem. A digital robust controller that minimises an upper bound to the ℋ∞ performance of the closed-loop networked control system (NCS) is determined. The design conditions rely on a particular parameter-dependent Lyapunov function and are expressed as bilinear matrix inequalities (BMIs) in terms of extra matrix variables, which may be explored in the search for a better system behaviour. Numerical examples illustrate the results.