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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.

This paper proposes a novel Non-Cooperative Distributed Model Predictive Control (NC-DMPC) strategy for collision avoidance of networked multiple Differential Drive Mobile Robots (multi-DDMRs). This strategy is based on Priority-Based NC-DMPC (PB-NC-DMPC). To avoid the loss of the prediction consistency caused by PB-NC-DMPC, a concept of urgency is introduced to DDMRs in the Networked Control Systems (NCS), and a corresponding priority queue is obtained by sorting these urgency values. Renumbering these priorities in descending order converts the partial order priorities into a topological order, which is a valid sequence for the DDMRs to solve their optimization problems. At last, the Sequential Convex Programming (SCP) is presented to solve the non-convex optimization problem resulting from the collision avoidance constraints. As a special application, the proposed strategy solves the problem of collision avoidance of Multi-DDMRs, compared to the original PB-NC-DMPC, the proposed strategy offers a more effective and safe performance in complex applications.

The dynamic event-triggered fault detection problem for discrete networked control systems with time-delay is investigated in this paper. Firstly, for reducing the triggering times, a new dynamic event-trigged is proposed. Secondly, an observer is constructed on the controller node to generate fault residual, and the mathematical model of the closed-loop systems is established by analyzing the sequence of the transmission signal. Thirdly, by constructing a suitable Lyapunov-Krasovskii functional, the sufficient stability conditions for the closed-loop networked control systems are derived. The computing method of the observer gain matrix, the controller gain matrix and the minimal disturbance repression index is provided. Finally, a casy study on the dynamic cart is employed to illustrate the merits of the proposed approach.

This article proposes a communication-efficient event-triggered time-delay control (ET-TDC) scheme, which is more intelligent, consumes fewer network resources, and is more suitable for practical applications, such as network control systems over bandwidth-limited communication channels. The proposed controller ensures a fast convergence rate and high tracking performance because it is based on TDCs that are well known for achieving high tracking performance. To maintain these properties, the proposed control scheme adopts a performance-preserving ET strategy, whereby the communication effort between the controllers and actuators can be significantly reduced. The ET condition of the proposed controller is devised to ensure system stability by using a Lyapunov function. Finally, the performance of the proposed ET-TDC is demonstrated through a numerical simulation and an experiment using a two-link robot manipulator. [ABSTRACT FROM AUTHOR]

Time triggered communication provides fault tolerance and determinism in a distributed dependable real time systems. These systems crucially depend on fault tolerant clock synchronization. The article presents simulation of fault tolerant averaging algorithm for clock synchronization and it's modification for improved convergence. We present the simulation results of synchronization algorithm to verify fault tolerance and convergence to a single time base. By modification, we show how a two node system can also be synchronized eliminating the criteria of minimum three nodes. This article also reports a custom time triggered protocol named as deterministic fault tolerant communication protocol particularly suitable for mission critical applications or safety-critical control applications such as in automotive “by-wire” and aerospace systems. The article also presents a different approach for membership service which is based on majority voting and can be used in systems based on time triggered architecture. [ABSTRACT FROM AUTHOR]

This work focuses on the dissipative analysis and quantized sampled-data control design issues for T-S fuzzy networked control system (TSFNCS) under stochastic cyber-attacks (SCAs), which have strong application backgrounds and significant theoretical research value in the field of network security. For this work, a novel time-delay-product relaxed condition (TDPRC) is introduced, which can obtain the slack constraints based on the delay information. Then, by fully considering the delay and sampling time point information, an improved boundary looped-functional (BLF) is developed to acquire more information on the Lyapunov-Krasovskii functional (LKF). In addition, based on the relationship between the sampling moments $(t_{k+1}-t)\eta ^{T}_{3}(t)$ and $(t-t_{k})\eta ^{T}_{4}(t)$ in $V_{c}(x_{t})$ , the obtained constraints may be further relaxed. Next, a new criterion and the corresponding algorithm are established using reciprocally convex matrix inequality (RCMI), proper integral inequalities, and the linear convex combination method (LCCM). In addition, a new quantitative sample data (QSD) controller under SCA is designed to ensure that TSFNCS is asymptotically stable (AS) and dissipative. Finally, the experiment of the truck-trailer system (TTS) dynamics equations proves the correctness of the theory proposed in this paper. [ABSTRACT FROM AUTHOR]

This paper considers the resilient $H_{\infty }$ dynamic control of nonlinear uncertain systems over a network assuming random communication packet dropouts, a subject which is seldom considered in the current literature for such uncertain systems. The uncertainties in the system and the controller are real, time-varying and norm bounded. Bernoulli distribution with white sequence is used to model the random packet losses with assumed conditions on the probability distribution. The resilient controller designed is an observer-based dynamic. The resulted closed-loop system is exponentially mean square stable and the $H_{\infty }$ performance is less than a prescribed level $\gamma $ for all admissible uncertainties. New sufficient conditions for the existence of such a controller are presented and proved based on the linear matrix inequalities (LMIs) approach. A numerical example is presented to demonstrate and show the effectiveness of the developed theory.

Networked control systems can help build cost-effective and flexible industrial systems. A system that can function while being immune to cyberattacks is necessary. A method called fixed redundant path selection (FRPS) has been proposed to detect and mitigate data tampering attacks in a networked motion control system. This system contains redundant forward network paths from the controller to the motor sides to detect the attacked path by comparing the values that are received through respective paths. Then, a path selector on the motor side chooses a value on the path that is not attacked based on the majority decision. Increasing the number of redundant paths improves the detection performance of simultaneous attacks against multiple paths. However, it also increases the amount of traffic because the same data are transmitted to all of the redundant paths. This study proposes a dynamic redundant path selection (DRPS) method to balance the detection performance and the amount of traffic. The proposed method initially applies three redundant paths and changes the number of redundant paths to five only when the path selector detects a difference among the received values for the three paths. The experiments confirm that the proposed DRPS outperforms the conventional FRPS. The former can detect and mitigate the data tampering attacks while reducing the number of network paths during tampering detection when the system is exposed to simultaneous attacks against up to two of the redundant paths.

The energy consumption of network interfaces in networked control systems (NCSs) must be reduced for sustainability. The sleep mechanisms of energy-efficient network interfaces for networked motor control systems, in which controller and motor devices are connected by communication networks, have attracted much interest in recent years. They reduce the energy consumption of network interfaces by making the transmitters installed on the controller and motor devices enter a sleep period when no data are to be transmitted. In a conventional send-on-delta (SoD)-based sleep control method, the network interfaces decide when to enter the sleep period based on the variations of the control input and response values. Although this method effectively reduces the communication rate for reducing energy consumption, it does not explicitly consider the quality of performance (QoP) or control performance such as tracking errors. In high-precision motion control systems, ensuring a certain QoP level is crucial. This study proposes a QoP-aware sleep control method for energy-efficient networked motor control systems to maintain the QoP at a certain level while operating the sleep mechanism. Here, the QoP is defined as the tracking error between the command and the response values. In the proposed method, network interfaces decide when to enter the sleep period based on the tracking error. Experimental results confirm that the QoP-aware sleep control method outperforms the SoD-based sleep control method in terms of the tracking errors (i.e., integral square error and steady-state error) at the expense of increased communication rates.

This study proposes an adaptive gradient descent algorithm for networked control systems, where the systems encounter a time-delay. To estimate the parameters and time-delay simultaneously, a redundant rule based method is introduced to transform the system into an augmented model. Then, the parameters are estimated by using an adaptive gradient descent algorithm. Finally, the true parameters and time-delay can be obtained based on the parameter estimates of the augmented model. A simulation example is proposed to validate the effectiveness of the proposed algorithm.

This brief studies the problem of preserving state and control privacies in a networked system where the plant is a constrained discrete-time linear system with bounded disturbances. Our approach to this problem is a privacy-preserving control scheme which assigns integer tokens to the combination of affine transforms and qualifying polytopes within state constraints. Specifically, we utilize the piecewise affine property of a feedback control law obtained with the explicit model predictive control technique and design tokenized affine transforms for the control law and the polytopic partition of its domain. The qualifying polytopes are referred to as subregions and virtual subregions which are generated within the partitioned domain mentioned above. We show that the proposed scheme is semantically secure against privacy extraction by an eavesdropper. Simulation results demonstrate the validity of the proposed scheme in preserving state and control privacies. [ABSTRACT FROM AUTHOR]

This brief considers the analysis of networked structural control systems with measurement loss. This is modeled as a sampled-data system that integrates the discrete-time operation of the controller with a fast-sampling approximation of the continuous-time structural (plant) dynamics. Random measurement loss in each channel due to the use of the wireless transmission is modeled as a Bernoulli process. This leads to a discrete-time, Markov jump linear model for the feedback system. An H2-norm analysis is proposed to assess the stability and the performance of the structural control. An example of a three-story building model is used to illustrate this approach. The H2-norm results are shown to be in agreement with the numerical simulations. The analysis can, thus, be used to assess various design choices. For example, the relationship between the probability of signal loss and the H2-norm depends on the method used to handle the signal loss. Moreover, the analysis shows that, for a jump controller setup using steady-state Kalman gains, the system can become unstable at very small probabilities of signal loss. [ABSTRACT FROM AUTHOR]

In this article, a robust leader–follower tracking control scheme is proposed to deal with the stochastic multi-unmanned aerial vehicle (UAV) networked team tracking control problem to achieve a prescribed $H_{\infty }$ robust tracking performance. By taking the leader’s desired path and every UAV networked system into account, the leader–follower tracking error networked system is constructed by arranging the UAVs network systems into a leader–follower formation. To effectively reduce the effect of the external disturbance on the team tracking process, a robust $H_{\infty }$ controller is proposed. With the help of the Itô–Lévy formula, the robust team tracking control design of the multi-UAV system is transformed to a Hamilton–Jacobin inequality (HJI)-constrained optimization problem. Since the HJI constraint cannot be easily solved, the Takagi–Sugeno (T–S) fuzzy interpolation method is employed to approximate the nonlinear networked system with a set of local linearized stochastic networked systems to simplify the design procedure. By the proposed T–S fuzzy control method, the $H_{\infty }$ robust leader–follower tracking control design of the stochastic multi-UAV networked system can be transformed to equivalent linear matrix inequalities (LMIs)-constrained optimization problem which can be efficiently solved by using the convex optimization techniques. Finally, a design example is given with simulation to illustrate the design procedure of the robust team tracking control of desired attitude and path and validate the effectiveness of the proposed robust $H_{\infty }$ team tracking control method of the multi-UAV networked system. [ABSTRACT FROM AUTHOR]

In this paper, the optimal linear filtering problem for linear discrete-time stochastic systems with random matrices, correlated noises and packet dropouts is studied where the random matrices are real and appear both in the the state and measurement equations. Using an equivalent transformation for random matrices and some results presented in this paper, an optimal linear filter for the system under consideration is developed. The developed optimal filter has a recursive pattern, and its computational complexity does not change with time. Number examples with simulation results are given to examine the performance of the developed optimal linear filter.

This paper investigates the hybrid-driven-based networked control for an offshore steel jacket platform subject to external wave forces. A hybrid driven strategy is introduced to deal with the problem of networked control for offshore platforms. Then, the networked closed-loop system is modeled as a stochastic delay system. Based on this model, a stability criterion is derived using the stochastic control theory and the Lyapunov-Krasovskii functional method. Simulation results show that the hybrid-driven-based networked H∞ controller is effective to suppress the vibration of the platform and save the limited network resources as well. Moreover, the designed controller is flexible in terms of maintaining a balance between performance requirements of the offshore platform and the utilization of communication network bandwidth.

In this paper, a cyber-physical digital signature creation method and a resilient load frequency control approach are proposed to improve the security of the existing SCADA protocols used in the load frequency control of interconnected power systems. In specific, the dynamic model of the power system is used to predict the future states of the system and the statistics of a number of future states are calculated and used as the dynamic hash to determine the integrity of the data communicated between remote telemetry units and the power system SCADA control center. The proposed algorithm has inherently the cyber-physical characteristics and enhanced robustness to collisions without adding a larger overhead to the message frame of the packets in current SCADA protocols. To compensate for the possible performance degradation and instability of the power system caused by corrupted data, a model-based resilient load frequency controller is designed for the smart grid. The maximum interval between two consecutive feedback updates in the model-based control scheme is obtained for securing the stability of the power system. The investigation of three types of integrity attacks on a two-area power system shows that the proposed model-based digital signature attack detection scheme is able to detect even a little inconsistency of the communicated data. By using the designed resilient load frequency controller, the stability and dynamic performance of the smart grid are guaranteed.

Networked control systems (NCSs), in which controllers and actuators are connected by communication networks, have been utilized in both industrial and consumer applications. In addition, sleep-based energy-efficient network interfaces have been developed for constructing a green networked society. The combination of the NCSs and energy-efficient network interfaces is a promising approach to reduce the power consumption of NCSs. However, sleeping of the network interface results in loss of data to be transmitted between a controller and an actuator. The sleep-induced data loss causes degradation of control performance. Moreover, NCSs originally include network delay for both forward and feedback paths, which also degrades control performance. This paper proposes a time-delay and data-loss compensation method using a modified communication disturbance observer (MCDOB) for NCSs with sleep-based energy-efficient interfaces. The proposed MCDOB can simultaneously compensate for not only the network delay but also sleep-induced data loss as a disturbance, whereas a conventional communication disturbance observer (CDOB) considers only network delay or network-induced data loss and cannot be directly introduced into the NCSs with sleep-based energy-efficient interfaces. Experimental results show that the proposed method with MCDOB outperforms the conventional method without the MCDOB in terms of integral square error (ISE) and communication rate, which indicates the power consumption of network interfaces.

The stabilization problem for a class of discrete network control system with time-delay and packet loss in both S-C side and C-A side is researched in this paper. Firstly, two independent discrete Markov chains are used to describe the network time-delay from sensor to controller and the network time-delay from controller to actuator. Two random variables obeying the Bernoulli distribution are employed to describe the packet loss between the sensor and the controller and the packet loss between the controller and the actuator. Secondly, a mathematical model for closed-loop system is established. By constructing the appropriate Lyapunov-Krasovskii functional, the sufficient conditions for the existence of the controller and observer gain matrix are obtained under the condition that the transition probabilities of S-C time-delay and C-A time-delay are both partly unknown. Finally, two examples are exploited to illustrate the effectiveness of the proposed method.

The present study discusses the consensus control of dual-rate multi-agent systems, where the sampling/communication interval of quantized data is an integer multiple of the control interval. A conventional multi-agent system uses a dynamic quantizer which is designed in a single-rate system where the intervals are equal, i.e., the control interval length is the same as the communication interval length. However, a dynamic quantizer designed in a dual-rate system is expected to have improved control performance. In the present study, an objective function is divided into a quantization term, which is related to the quantization error, and the remaining term. The proposed dual-rate dynamic quantizer is designed such that the quantization term is minimized. Finally, in numerical examples, the proposed dual-rate method is quantitatively evaluated by comparing with the conventional single-rate method, and the effectiveness of the proposed method is demonstrated.

Over the past decades, the synchronization of complex networks with directed topologies has received considerable attention owing to its extensive applications in the realistic world. Design of proportional-integral–derivative (PID) control protocols for achieving synchronization with directed networks is known to be a challenging task. The purpose of this paper is to establish a connection between the PID control protocols and synchronization of complex dynamical networks with directed topologies. Based on the classical complex network model, we investigate global synchronization with PD controller of a balanced strongly connected directed network and global synchronization with PI controller of a strongly connected directed network, and a directed network containing a spanning tree, respectively. Several sets of sufficient conditions are established under which the network reaches global synchronization. The simulation examples are presented to verify the efficiency of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper addresses the co-design problem of a fault detection filter and controller for a networked-based unmanned surface vehicle (USV) system subject to communication delays, external disturbance, faults, and aperiodic denial-of-service (DoS) jamming attacks. First, an event-triggering communication scheme is proposed to enhance the efficiency of network resource utilization while counteracting the impact of aperiodic DoS attacks on the USV control system performance. Second, an event-based switched USV control system is presented to account for the simultaneous presence of communication delays, disturbance, faults, and DoS jamming attacks. Third, by using the piecewise Lyapunov functional (PLF) approach, criteria for exponential stability analysis and co-design of a desired observer-based fault detection filter and an event-triggered controller are derived and expressed in terms of linear matrix inequalities (LMIs). Finally, the simulation results verify the effectiveness of the proposed co-design method. The results show that this method not only ensures the safe and stable operation of the USV but also reduces the amount of data transmissions. [ABSTRACT FROM AUTHOR]

The distributed control architecture is expected to dominate the gas turbine engine (GTE) control systems in future, in which the sensors and actuators are connected to the controllers via a network. Hence, the control problem of network-enabled high-performance distributed engine control (DEC) becomes important in modern gas turbine control systems. Due to the properties of the network, the packet dropouts must be considered. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a $H_\infty $ output feedback under random packet-dropouts. The sufficient robust mean-stable conditions are derived via the Lyapunov stability theory and linear matrix inequality approach. In addition, the effectiveness of the presented method is illustrated through a series of simulations.

To obtain accurate trajectory tracking with robustness and faithful force feedback in a practical application, a sliding mode controller (SMC) combined with a compensation controller based on a nonlinear disturbance observer (DOB) is proposed. The DOB estimates the disturbances arising mainly from the uncertain dynamic model of a surgical manipulator, frictional forces and external interaction forces, and compensates for these disturbances in the control law. Accordingly, it alleviates the chattering problem caused by the SMC and improves tracking performance. The surgical teleoperation system using the proposed SMC-DOB is proved to be asymptotically stable using Lyapunov theory. The simulation and experiment results show that the surgical manipulator with the SMC-DOB can better track the trajectory of the master even in the presence of disturbances and the interaction forces between the instrument and the patient's tissues are faithfully presented to the surgeon.

This article presents a resilient model predictive control (MPC) framework to attenuate adverse effects of denial-of-service (DoS) attacks for cyber–physical systems (CPSs), where the system dynamics is modeled by a linear time-invariant system. A DoS attacker targets at blocking the controller to actuator (C–A) communication channel by launching adversarial jamming signals. We show that, in order to guarantee exponential stability of the closed-loop system, several conditions for resilient MPC should be satisfied. And these established conditions are explicitly related to the duration of DoS attacks and MPC parameters such as the prediction horizon and the terminal constraint. Two key techniques, including the $\mu$ -step positively invariant set and the modified initial feasible set are exploited for achieving exponential stability in the presence of DoS attacks. Moreover, the maximum allowable duration of the DoS attacker is also obtained by using the $\mu$ -step positively invariant set. Finally, the effectiveness of the proposed MPC algorithm is verified by simulated studies and comparisons. [ABSTRACT FROM AUTHOR]

In this paper, periodic event-triggered sampling and dual-rate control techniques are integrated in a wireless networked control system (WNCS), where time-varying network-induced delays and packet disorder are present. Compared to the conventional time-triggered sampling paradigm, the control solution is able to considerably reduce network utilization (number of transmissions), while retaining a satisfactory control performance. Stability for the proposed WNCS is ensured using linear matrix inequalities. Simulation results show the main benefits of the control approach, which are experimentally validated by means of an unmanned-aerial-vehicle-based test-bed platform. [ABSTRACT FROM AUTHOR]

Future gas turbine engine control systems will be based on a distributed architecture in which the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) system is dependent on the network performance. The network-induced time delay may degrade the performance of the closed-loop systems and even destabilize the systems if the controllers are designed without considering the effects of the delay. This paper introduces a new method to estimate the maximum tolerance of the time delay for analysis of the stability of the GE T700 turboshaft engine DEC system. The sufficient conditions for stability are derived and dynamic output feedback controllers for the turboshaft engine are applied. Hardware-in-the-loop simulation illustrates the effectiveness of the presented method.

Under the mild assumption that only the sampled-data output information about the master system is available, synchronization of networked master–salve system consisting of a high-order master system and a low-order slave system is investigated in this paper. Specifically, the dynamics of the master system and those of the slave system are allowed to be characterized by heterogeneous nonlinear systems. The communication between these two systems are transmitted by multiple sensors over a communication network, while at each sampling instant, only one sensor is allowed to transmit its current information to the controller’s side according to some carefully designed scheduling protocols. To achieve master–salve synchronization, the stochastic scheduling and the Round-Robin scheduling protocols are, respectively, proposed and utilized. By appropriately designing observer and controller for the slave system, some sufficient synchronization criteria regarding to the gain matrices, sampling intervals and communication delays are derived for the closed-loop master–salve system under respectively the stochastic scheduling and the Round-Robin scheduling protocols. Last, two numerical examples are simulated to validate the effectiveness of the theoretical results. [ABSTRACT FROM PUBLISHER]

This paper considers the master and slave synchronization control for bilateral teleoperation systems with time delay and backlash-like hysteresis. Based on radial basis functions neural networks’ approximation capabilities, two improved adaptive neural control approaches are developed. By Lyapunov stability analysis, the position and velocity tracking errors are guaranteed to converge to a small neighborhood of the origin. The contributions of this paper can be summarized as follows: 1) by using the matrix norm established using the weight vector of neural networks as the estimated parameters, two novel control schemes are developed and 2) the hysteresis inverse is not required in the proposed controllers. The simulations are performed, and the results show the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

Smart homes reduce human intervention in controlling the heating ventilation and air conditioning (HVAC) systems for maintaining a comfortable indoor environment. The embedded intelligence in the sensor nodes is limited due to the limited processing power and memory in the sensor node. Cloud computing has become increasingly popular due to its capability of providing computer utilities as internet services. In this study, a model for the intelligent controller by integrating internet of things (IoT) with cloud computing and web services is proposed. The wireless sensor nodes for monitoring the indoor environment and HVAC inlet air, and wireless base station for controlling the actuators of HVAC have been developed. The sensor nodes and base station communicate through RF transceivers at 915 MHz. Random neural network (RNN) models are used for estimating the number of occupants, and for estimating the predicted-mean-vote-based setpoints for controlling the heating, ventilation, and cooling of the building. Three test cases are studied (Case 1—Data storage and implementation of RNN models on the cloud, Case 2—RNN models implementation on base station, Case 3—Distributed implementation of RNN models on sensor nodes and base stations) for determining the best architecture in terms of power consumption. The results have shown that by embedding the intelligence in the base station and sensor nodes (i.e., Case 3), the power consumption of the intelligent controller was 4.4% less than Case 1 and 19.23% less than Case 2. [ABSTRACT FROM PUBLISHER]

A simple distributed object model, called an asynchronous distributed object protocol (ADOP), was designed and implemented as middleware for a control system of a synchrotron radiation source. The ADOP replaces time-constrained parts of the control system that were previously based on the Java Remote Method Invocation (RMI) model. Under RMI’s synchronous communication, when a client executes a remote-method invocation for a device/component to be controlled on a remote server, the client is suspended until the server sends a result back to the client after completing the control sequence. Using the ADOP, even in a multi-client environment, clients are not blocked when they make remote-method invocations with an object parameter/return object that includes short control data associated with the event data, status data, and setting data for the devices/components. The clients can asynchronously receive resultant control data from the remote servers. Performance measurements obtained in experiments demonstrate that the ADOP had an execution time that was 1.4–13.1% of the RMI’s execution time. [ABSTRACT FROM AUTHOR]

Distributed generators (DGs) have been developing rapidly in power systems. Motivated by their intrinsic distributed nature, distributed cooperative control based upon local communication recently emerge as a preferred strategy. For instance, a cooperative power control strategy can regulate the active power from a cluster of DGs at a certain ratio of its maximal available power according to a dispatch command. However, such a networked control system is susceptible to both communication failure and cyber-attack, e.g., denial-of-service attack and deceptive attack. To address this potential problem, an attack-resilient cooperative control strategy is proposed in this paper. With a properly designed observation network, each DG can monitor the behaviors of all its in-neighbors, and gradually isolate the misbehaving DGs (when present) from the network as long as they do not collude with each other. Consequently, even certain DGs misbehave, the rest of them can together accomplish the control objective provided that the remaining communication network is still connected. Simulations of the IEEE standard 34-bus test feeder demonstrate effectiveness of the proposed strategy. [ABSTRACT FROM PUBLISHER]

This paper proposes an efficient way to handle fault in controller area network (CAN)-based networked control system (NCS). A fault in a bus line of CAN will induce a data error which will result in data dropout or time delay, and subsequently may lead to performance degradation or system instability. A strategy to handle fault occurrence in CAN bus is proposed to properly analyze the effect of the fault to CAN-based NCS performance. The fault occurrences are modeled based on fault interarrival time, fault bursts’ duration, and Poisson law. Using fault and messages’ attributes, response time analysis (RTA) is performed and the probability of control message missing its deadline is calculated. Utilizing the new error handling algorithm to replace the native error handling of CAN, the probability of a control message missing its deadline can be translated into the probability of data dropout for control message. This methodology is evaluated using steer-by-wire system of vehicle to analyze the effect of fault occurrences in CAN. It is found that the proposed error handling mechanism has resulted in better NCS performance and the range of data dropout probability for control message also could be obtained, which serves as crucial input for NCS controller design. [ABSTRACT FROM PUBLISHER]

This paper investigates the tracking and optimization problems for a class of industrial processes by utilizing output feedback fault-tolerant control (FTC) and predictive compensation strategy. At device layer, the tracking problem for device layer subsystems which subject to random failures and random network-induced delays is investigated. These two different random processes are modeled as Markovian chains. Device layer controllers are designed to guarantee the tracking performance at H\infty disturbance attenuation level. At operation layer, a nonlinear model predictive control (NMPC) strategy is proposed to stabilize the upper operation layer system. Then by considering the effect of radial basis function (RBF) performance index and random packet dropout phenomena, a predictive compensator is designed to guarantee the input-to-state practical stability (ISpS) of the resulting system. In addition, networked flotation processes are considered in the simulation part, and the simulation results further demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A self-triggered sampling scheme (STS) is proposed for a networked control system with consideration of data losses and communication delays. By making use of this scheme, the next sampling instant does not depend on online estimation of an event-triggered condition and the successive measurement of the state, and can be dynamically determined with respect to the transmitted packet, the desired control performance, and the allowable number of consecutive data losses and communication delays. Consequently, the sampling interval can be adaptively adjusted. Therefore, the communication burden can be greatly reduced and the energy efficiency can be much improved while preserving the desired H_\infty performance. An inverted pendulum and a one-area power system controlled over a wireless sensor network are given to illustrate the effectiveness of the proposed STS. [ABSTRACT FROM PUBLISHER]