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A multiagent system based distributed cooperative control is proposed for a dc microgrid. First, the multiagent system based control scheme is built, where each distributed energy resource unit is associated with a first-level unit control agent to deal with primary control and a secondary-level distributed cooperative control agents to implement secondary control. For the secondary control purposes of global voltage regulation and proportional current sharing, both voltage and current regulators are installed in each secondary-level agent. Their consensus secondary control protocols are designed by using the state information exchanged among only adjacent secondary-level control agents based on a switching topology communication network with time-vary delays. Then these protocols are applied into the associated first-level agent to structure an improved outer-loop droop controller. According to the reference set points corrected by the improved droop controller, an inner-loop voltage/current robust controller is designed in place of the conventional PI control to regulate the voltage and current of distributed energy resource unit. Finally, the validity of the proposed control is testified by means of simulation results.

In this paper, the potential improvement in performance of an NCS (Networked Control System) subject to variable delays controlled by means of an adaptive system is analyzed. An adaptive Smith Predictor has been used to compensate the effects of varying delays measured on the network. The NCS, closed over the Internet, has been implemented using a platform called NCS-CMUF, composed of local and remote stations. The plant used to carry out the experimental tests is consisted of an optical oven in which the luminosity loop is the main controlled variable whose time constant lies in the range of milliseconds. This paper highlights the importance of synchronization between the clocks of the local and remote stations to perform consistent measurements of network delays, in order to provide an active compensation of the effects of delays. The results show the effectiveness of adaptive Smith Predictor in coping with different delays and the performance improvements achieved with the proposed scheme.

The security issue in the state estimation problem is investigated for a networked control system (NCS). The communication channels between the sensors and the remote estimator in the NCS are vulnerable to attacks from malicious adversaries. The false data injection attacks are considered. The aim of this paper to find the so-called insecurity conditions under which the estimation system is insecure in the sense that there exist malicious attacks that can bypass the anomaly detector but still lead to unbounded estimation errors. In particular, a new necessary and sufficient condition for the insecurity is derived in the case that all communication channels are compromised by the adversary. Moreover, a specific algorithm is proposed for generating attacks with which the estimation system is insecure. Furthermore, for the insecure system, a system protection scheme through which only a few (rather than all) communication channels require protection against false data injection attacks is proposed. A simulation example is utilized to demonstrate the effectiveness of the proposed conditions/algorithms in the secure estimation problem for a flight vehicle. This work was supported in part by the Royal Society of the UK, the National Natural Science Foundation of China under Grant 61329301, the Australian Research Council Discovery Project under Grant DP160103567, and the Alexander von Humboldt Foundation of Germany .

Summary This paper presents an event-triggered predictive control approach to stabilize a networked control system subject to network-induced delays and packet dropouts, for which the states are not measurable. An observer-based event generator is first designed according to the deviation between the state estimation at the current time and the one at the last trigger time. A predictive control scheme with a selector is then proposed to compensate the effect of network-induced delays and packet dropouts. Sufficient conditions for stabilization of the networked control system are derived by solving linear matrix inequalities and the corresponding gains of the controller and the observer are obtained. It is shown that the event-triggered implementation is able to realize reduction in communication and save bandwidth resources of feedback channel networks. A simulation example of an inverted pendulum model illustrates the efficacy of the proposed scheme.

Recent studies have shown that traffic safety and efficiency can be substantially improved by vehicle platooning , in which vehicles periodically broadcast their kinetic status to neighbors, known as beacon message dissemination . As a networked control system, vehicle platoon has attracted significant attention from both the control and networking areas. However, few studies consider the practical traffic scenario with both platoons and individual vehicles, and the proposed beaconing schemes lack the deep understanding of relationship between the beaconing performance and the requirements of the control mechanism. To address these challenging issues, we propose a joint control–communication design to achieve reliable vehicle platooning in a more realistic traffic scenario, wherein the traffic consists of both platoons and individual vehicles, and both periodic beacon messages and event-based safety messages shall be delivered together. Specifically, we first develop a comprehensive control-theoretical analysis to understand how the vehicular communication can affect features of platoon driving; based on the understanding, we then propose and analyze an adaptive platoon-based message dissemination scheme; finally, we conduct extensive numerical experiments to validate the effectiveness of the protocol and to confirm the accuracy of the our theoretical analysis.

Avast range of technological systems-from aerospace vehicles to chemical processes to Segways-depend on feedback control. These applications typically rely on a combination of classical and modern control techniques, logic for mode switching, and diagnostics for fault detection to ensure safety and reliability, all of which are validated and verified through simulation and testing. A feedback control system is the quintessential cyberphysical system, in which real-time digital computing elements interact bidirectionally with the full complexity of the real world through noisy transducers and limited communication channels [1]. In many applications, the control system is crucial to safe operation, and the potential benefits of new ideas and techniques for feedback control must be weighed against the risk of unanticipated response and/or failure.

The paper analyses a networked control system consisting of a linear time-invariant system with a static feedback nonlinearity, subject to large delays in the feedback loop. This model is valid for example in wireless data flow control, where a saturation occurs since the flow is one-directional. The present paper extends previous results by proving necessity, in case the loop gain is uniformly less than one. The results are validated and illustrated in a simulation study.

This paper concentrates on investigating the robust L1 output tracking control problem for the networked control systems described by Takagi–Sugeno fuzzy model with distributed delays and uncertainties. First, according to the parallel distributed compensation and Lyapunov theory, a fuzzy delay-dependent and basis-dependent Lyapunov–Krasovskii function that contributes to reducing the conservatism is constructed. Second, the L1 performance criterion guaranteeing the asymptotic stability of the corresponding tracking control system and satisfying the prescribed tracking performance is derived. Furthermore, the output tracking control problem is converted into a convex optimisation problem. Finally, the results from simulation certify the effectiveness of the designed controller.

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.

In this paper, the fault detection problem is studied in finite frequency domain for constrained networked systems under multi-packet transmission. The considered transmission mechanism is that only one packet including parts of the measured information can be transmitted through the communication channel and their accessing is scheduled by a designed stochastic protocol. Then by virtues of the introduced performance indices in finite frequency domain, a novel effective fault detection scheme is presented, in which the fault detection filters completing the task with partially available measurements are designed to make sure that the residual is sensitive to the reference input and the fault in faulty cases and robust to the reference input in fault-free case. Further, convex conditions in terms of time-domain inequalities are developed to handle the proposed fault detection scheme. The theoretical results are validated by the simulation to detect the sensor fault on a lateral-directional aerodynamic model.

This paper focuses on the issues of the security of networked control systems by summarizing recent progress in secure control of this research and application area. We mainly discuss existing results, especially in modeling issues, of three aspects: (1) attack mechanisms and their impacts on control systems, (2) the identification and design of attacks, and (3) secure estimation and control strategies. A conclusion is drawn at the end of this paper. In addition, several promising research tendencies of the development for secure control in networked control system are presented.

A model-based event-triggered control scheme for nonlinear constrained continuous-time uncertain systems in networked configuration is presented in this paper. It is based on the combined use of model-predictive control (MPC) and integral sliding-mode (ISM) control, and it is oriented to reduce the packet transmission over the network both in the direct path and in the feedback path, in order to avoid network congestion. The key elements of the proposed control scheme are the ISM local control law, the MPC remote controller, a smart sensor, and a smart actuator, both containing a copy of the nominal model of the plant. The role of the ISM control law is to compensate matched uncertainties, without amplifying the unmatched ones. The MPC controller with tightened constraints generates the control component oriented to comply with state and control requirements and is asynchronous since the underlying constrained optimization problem is solved only when a triggering event occurs. In the paper, the robustness properties of the controlled system are theoretically analyzed, proving the regional input-to-state practical stability of the overall control scheme.

In this paper, an efficient output feedback predictive control synthesis based on a prespecified observer for networked control systems is presented. The process of random packet loss between the controller and the actuator is described as Markov chain, and a missing data compensation strategy is induced to cope with the poor performance caused by fading links. The provided model predictive control algorithm optimizes an infinite-horizon objective and parameterizes the infinite-horizon control moves into a free control move followed by output feedback. Further, the corresponding constraints about recursive feasibility and stochastic stability are given by utilizing the linear matrix inequality technique. A numerical example is given to illustrate the applicability of the proposed method.

This paper is concerned with the problem of event-triggered dynamic output-feedback H∞ control for networked control system with sensor and actuator saturations. The event-triggered scheme combined with sensor saturation is first introduced to judge whether the newly sampled signal should be transmitted to the dynamic output-feedback controller or not. Under this scheme, the concurrent closed-loop system is first modeled as a control system with an interval time-varying delay and nonlinear items. Through constructing the Lyapunov–Krasovskii functional and employing linear matrix inequality approach, sufficient conditions for H∞ asymptotical stability are derived for the networked control system; furthermore, under the above stability condition, a dynamic output-feedback controller and the corresponding event-triggered parameters are co-designed through linear matrix inequality approach. Lastly, a numerical example is employed to prove the practical utility of this method.

In this paper, with the help of the Youla parameterization, the realizations of feedback control systems are discussed which results in a preferable and more convenient way to realize plug-and-play (PnP) control without modifying pre-designed control systems. Furthermore, based on the equivalence of different realizations of the Youla parameterization, a link between the standard feedback and the observer-based state feedback control system is given so that the well developed observer-based control techniques, like LQG/H2 control etc., can be achieved in the standard feedback control system via PnP control design. The effectiveness of the proposed PnP design schemes is verified using a direct current (DC) motor benchmark system.

This paper addresses the problem of fault-tolerant control in large-scale systems wherein the subsystems have to assure together a steady state control goal. It is considered that the faulty subsystem cannot be reconfigured locally and consequently, as a fault occurs, the command inputs of the fault-free systems have to be modified in order to guarantee the original control goal in the presence of fault as well. The proposed control strategy estimates the fault-induced modifications in the output of the faulty subsystem and, based on this information, recomputes the command inputs of the fault-free systems. To compensate the effect of the fault propagation through the physical interconnections, the local controllers of the subsystems are augmented with an external integral control loop. The stability and the networked implementation of the reconfiguration strategy are also treated. Simulation results are provided to show the applicability of the proposed fault-tolerant control strategy.

In this paper, the optimal H∞ control of a linear time invariant (LTI) networked control system (NCS) over a lossy network is analyzed. Specifically we consider a TCP-like data network where packet drops are modelled using a two-state Markov process. By employing the theory of dynamic games, a state-feedback H∞ controller is obtained. It is shown that, subjected to a suitable H∞ disturbance attenuation level and suitable packet loss probabilities, such a controller exists for both finite and infinite horizon cases. We also show the asymptotic stability of the NCS in the mean-square sense. Finally a numerical example is presented to demonstrate our work.

The effect of jamming attacks on the stability of a networked control system is explored. In this networked system, control input packets are assumed to be transmitted on a wireless channel that faces jamming attacks by a malicious agent. Probability of transmission failures on this channel depends on the power of the interference signals emitted by the jamming attacker. We investigate the case where the attacker’s interference power is time-varying but bounded in average. We obtain almost sure asymptotic stability conditions for the closed-loop system. For obtaining these stability conditions, we utilize nondecreasing and concave functions of the attacker’s interference power that upper-bound the transmission failure probability. We present a numerical example to demonstrate the efficacy of our results.

In this paper an output-based model predictive controller for linear time-invariant discrete-time networked control systems subject to constraints is studied. In the networked control system the control loop is closed over a communication network between sensor and controller as well as controller and actuator. An output-based controller using a Luenberger observer for reconstruction of the system state is designed. For both communication networks event-triggers are utilized to reduce the communicational burden. Recursive feasibility of the control law is provided by robust control methods. Moreover, asymptotic stability of the closed-loop system is guaranteed. A simulation example illustrates that the proposed method can reduce the network utilization significantly.

In this paper, we study consensus seeking for a class of linear multi-agent systems (MAS) subject to the inevitable imperfections of packet-based networked communication. These imperfections include unknown non-uniform time-varying transmission delays and limited communication resources. To reduce the utilization of communication resources, we propose a dynamic event-triggered control scheme resulting in aperiodic transmission of information between agents. The proposed framework leads to event-triggered controllers that guarantee the MAS to asymptotically reach consensus, strictly positive lower bounds on the inter-event times and robustness for unknown non-uniform time-varying delays in terms of maximum allowable delays.

Digital networked control systems are of growing importance in safety-critical systems and perform indispensable function in most complex systems today. Networked degradations such as transmission delay and packet dropout cause such systems to fail to satisfy performance requirements, and eventually affect the overall reliability. It is necessary to get a model to verify and evaluate the system reliability in early design phase, prior to its implementation. However, existing probabilistic models only provide partial descriptions of such coupled networks and control system. In this paper, a new stochastic model represented by linear discrete-time approach is proposed, considering data packet transmissions in both channels: controller-to-actuator and sensor-to-controller. Different from pervious works, the historical behaviors of networked degradations are modeled by multistate Markov chains with uncertainties, releasing the assumption that faults of all periods are independent of each other. The concept of domain requirements for such systems is considered here, contributing to the integration of control and reliability engineering. Methodologies for quantitatively assessing the reliability of the single- and sequential-control goal are derived from the Monte Carlo method. An example of an industrial heat exchanger digital networked control system is provided to illustrate the effectiveness of the model and method.

To manage with large communication delays in the presence of scheduling protocols from sensors to actuators, the time-delay approach to continuous-time decentralized NCSs has been developed in Chap. 7. The results of Chap. 7 are confined to stability analysis. This chapter is devoted to extend the time-delay approach to decentralized stabilization and \(H_{\infty }\) control of large-scale discrete-time systems with multiple local communication networks connecting sensors, controllers and actuators.

To maintain a reliable and stable power grid there must be balance between consumption and production. To achieve power balance in a system with high penetration of distributed renewable resources and flexible assets, these individual system can be coordinated through a control unit to become part of the power balancing effort. Such control strategies require communication networks for exchange of control loop information. In this work, we show how a congested communication network can have a dramatic impact on the control performance of such a power balancing controller. To alleviate potential stability issues and increase control performance, an adaptive control design is proposed together with a communication network state estimation algorithm. Extensive simulation studies on a realistic model of a low voltage residential grid, using network traces obtained from a real powerline network, show significant performance improvement when the adaptive controller is used.

This paper addresses distributed coordination and cooperation control for networked mobile manipulators over a jointly connected topology with time delays. First, tracking control is proposed to guarantee the position and velocity synchronization of the networked mobile manipulators, while keeping a formation. For cooperation control, the decoupled dynamics is considered so that the task and null space of the mobile manipulators can be designed to achieve different missions. For end-effector motion, synchronization control works in combination with force controls to ensure that the network of mobile manipulators achieves cooperative manipulation and transportation. The motion of the mobile bases is controlled in the null space, which can be designed to track a trajectory, avoid colliding with obstacles, and achieve velocity consensus without influencing the main task. Numerical examples are addressed to demonstrate the performance of the proposed networked robotic system.

Summary This paper is devoted to the problem of designing a sparsely distributed sliding mode control for networked systems. Indeed, this note uses a distributed sliding mode control framework by exploiting (some of) other subsystems' information to improve the performance of each local controller so that it can widen the applicability region of the given scheme. To do so, different from the traditional schemes in the literature, a novel approach is proposed to design the sliding surface, in which the level of required control effort is taken into account during the sliding surface design based on the ℋ2 control. We then use this novel scheme to provide an innovative less-complex procedure that explores sparse control networks to satisfy the underlying control objective. Besides, the proposed scheme to design the sliding surface makes it possible to avoid unbounded growth of control effort during the sparsification of the control network structure. Illustrative examples are presented to show the effectiveness of the proposed approach.

In this paper, we investigate a resilient control strategy for networked control systems (NCSs) subject to zero dynamic attacks which are stealthy false-data injection attacks that are designed so that they cannot be detected based on control input and measurement data. Cyber resilience represents the ability of systems or network architectures to continue providing their intended behavior during attack and recovery. When a cyber attack on the control signal of a networked control system is computed to remain undetectable from passive model-based fault detection and isolation schemes, we show that the consequence of a zero dynamic attack on the state variable of the plant is undetectable during attack but it becomes apparent after the end of the attack. A resilient linear quadratic Gaussian controller, having the ability to quickly recover the nominal behavior of the closed-loop system after the attack end, is designed by updating online the Kalman filter from information given by an active version of the generalized likelihood ratio detector.

This paper addresses the problem of robust tracking control of networked control systems with communication constraints (network-induced delay, packet dropouts, and packet disorder) and external disturbance. A novel networked predictive control algorithm based on k -order adaptive discrete-time sliding-mode control ( k -ADSMC) is proposed. The ADSMC, which can self-adapting adjust sliding-mode parameters and ensure faster convergence, is designed based on the error and error difference of tracking output. Furthermore, k -ADSMC is designed, which uses the estimated disturbance as weight factors and synthesizes the sliding- mode values of all k times, in order to improve the robust of tracking control. Finally, the stability of the system is proved, and a dc motor servo system is utilized to verify the effectiveness of the proposed method.

In this paper, we study networked control systems in the presence of Denial-of-Service (DoS) attacks, namely attacks that prevent transmissions over the communication network. The control objective is to maximize frequency and duration of the DoS attacks under which closed-loop stability is not destroyed. Analog and digital predictor-based controllers with state resetting are proposed, which achieve the considered control objective for a general class of DoS signals. An example is given to illustrate the proposed solution approach.

We present a unified formalism for multiagent networked control and estimation with scheduling, delays, and packet loss in the communication channels between the controller and distributed sensors and actuators. The modular framework is a combined construction of a stochastic jump linear system (JLS) description of the plant and network effects, a Kalman filter-based estimator, and packetized predictive control, a receding horizon optimization technique with buffering at the actuator. Integration of these elements enables the synthesis of a novel estimation technique that generalizes prior approaches for control and measurement packet loss to the case with schedules, delays, control buffering, and most importantly, delayed and lossy control packet acknowledgments (ACKs). The JLS framework allows a clean separation of jump variable estimation and a posteriori state estimation using a backup-and-rerun strategy, and can handle variable-length ACK histories for multiple independent control communication channels. Finally, we derive modified covariance priors for the filter that account for uncertainty in the control action applied at the vehicle when ACKs are not available and control buffers are used. Simulations with single vehicle and multivehicle systems demonstrate the methods and show the benefits of utilizing delayed and lossy ACKs.

Day by day, networked control system (NCS) methods have been promoted for distributed closed-loop control systems. Interestingly, the integration of control and computing theories enhanced the development of networked control systems through remote control for wide applications employing the internet. Two further directions to networked control technology are Leader-Follower systems and model predictive control systems. Cloud control system is looked at an extension of networked control systems (NCS) using internet of things (IOT) methodologies. In this paper, a comprehensive literature survey of the new technology of control systems application performed on cloud computing is presented.

This paper addresses the output feedback stabilization problem for discrete-time networked control systems with imperfect input channels, i.e., the controller-actuator channels, where both quantization error and packet dropout are involved. A stabilizability condition is first derived for the single-input-single-output (SISO) case. It is shown that stabilization over quantized lossy channel actually involves a trade-off between robust stability control and robust performance control. Furthermore, the results are expanded to triangularly decoupled multiple-input-multiple-output (MIMO) systems and a necessary and sufficient condition is deduced, which also exhibits a compromise between robust stability control and robust performance control in the individual channel as echoing the SISO case.

This brief investigates the data-based networked control problem of a class of nonlinear systems, where random network-induced delays and packet dropouts in the feedback and forward channels are considered simultaneously and further treated as random round-trip time (RTT) delays. The main contributions of this brief are as follows: 1) To actively compensate for RTT delays, a novel compensation control scheme is proposed based on the control input design, and thus, only one control command needs to be transmitted to the actuator through the network; 2) an explicit sufficient condition is derived to ensure the stability of the resulting closed-loop system as well as a zero steady-state output error for a constant reference input; and 3) numerical simulation and comparison with existing methods are carried out to show the effectiveness of the proposed method.

This brief investigates the regulation problem for a class of networked nonlinear systems with measurement noise, where random data dropouts in both the feedback and forward channels are considered. To actively compensate for the two-channel data dropouts, a data-driven networked compensation control method is proposed, which consists of two aspects: 1) to calculate a control increment based on the measured output error in the controller and 2) to design a data dropout compensation strategy based on the latest control increment available in the actuator. The proposed method merely depends on the input and output data of the controlled plant, without using explicit or implicit information of its mathematical model. Moreover, only one control command needs to be transmitted in the forward channel at each time instant. A sufficient condition is derived to guarantee the closed-loop stability and output error convergence. Both numerical simulations and experimental tests are conducted to demonstrate the effectiveness of the proposed method.

In this paper we address the problem of wide-area control of power systems using Synchrophasor measurements in the presence of network delays. We propose a novel cyber-physical architecture that uses an arbitrated network control systems approach for mitigating the destabilizing effects of delays in power systems. The approach consists of: (1) utilization of Synchrophasor measurements from distributed measurements across different buses in the power network, (2) estimation of delays that control messages experience, (3) a delay-aware control design that explicitly accommodates the delays and judiciously utilizes estimated system states when needed, and (4) a switching control strategy that aborts the computation of control signals when delays exceed a certain threshold to improve resource utilization. While the control gains are determined using a centralized power system model and state feedback, it is shown that the delay-aware aspects of the proposed architecture allow both distributed measurements and distributed implementation of the control law. The results are illustrated using a 50-bus, 14-generator, 4-area power system model. The results clearly demonstrate that the proposed controller recovers the ideal system performance (such as deviations in frequency 3 mHz ) even in the presence of large intra-area and inter-area delays with a small amount of additional control effort. Using the proposed overrun strategy, the results also confirm that about 30% drops can be accommodated with the proposed arbitrated network control systems approach.

This paper aims to study on feedback control for a networked system with both uncertain delays and, packet dropouts and disturbances. Here, a so-called robust predictive control (RPC) approach is designed as follows: 1) delays and packet dropouts are accurately detected online by a network problem detector; 2) a so-called proportional-integral-based neural network grey model (PINNGM) is developed in a general form to be capable of forecasting accurately in advance the network problems and the effects of disturbances on the system performance; 3) using the PINNGM outputs, a small adaptive buffer (SAB) is optimally generated on the remote side to deal with the large delays and/or packet dropouts and, therefore, simplify the control design; 4) based on the PINNGM and SAB, an adaptive sampling-based integral state feedback controller is simply constructed to compensate the small delays and disturbances. Thus, the steady-state control performance is achieved with fast response, high adaptability, and robustness. Case studies are finally provided to evaluate the effectiveness of the proposed approach.

The closed-loop delay is one of the most important factors affecting the control performance of a wide-area control system (WACS), due to the network transmission of feedback and control signals. A prediction based hierarchical delay compensation (PHDC) method is proposed in this letter at the data processing level to deal with delays. For the control strategy on the top-level, all feedback and control information are real-time and transparent without consideration of delay. The PHDC method compensates the random and distributed delay effectively and reduces the impact of delays on the control performance.

The distributed control architecture becomes more and more important in future gas turbine engine control systems, in which the sensors and actuators will be connected to the controllers via a network. Therefore, the control problem of network-enabled high-performance distributed engine control (DEC) has come to play an important role in modern gas turbine control systems, while, 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 H∞ state feedback under random packet dropouts. The sufficient robust stable conditions are derived via the Lyapunov stability theory and linear matrix inequality approach. Simulations illustrate the effectiveness of the presented method.

In this paper, the problem of tracking control is studied for a class of nonlinear systems with actuator faults/failures. The control strategy has two steps. In the first step, a virtual control input is found using terminal sliding mode control which can easily tackle the output tracking control problem in a finite time. In the second step, control allocation (CA) transforms the virtual control signals to the real-control inputs. The CA problem is solved using a neural network which satisfies control constraints and during faults or failures redistributes the control signals to the healthy actuators. The effectiveness of the proposed control approach is demonstrated by the simulation results of the near space vehicle system.

This paper is concerned with the design and performance analysis of networked control systems, where random network-induced delay, packet disorder, and packet dropout in the feedback and forward channels are considered simultaneously and further treated as the round-trip time (RTT) delay. To actively compensate for the RTT delay, a networked predictive control scheme is designed based on the input-output difference equation model. For time-varying reference signals, the resulting closed-loop system can achieve the same output tracking performance and closed-loop stability as the corresponding local control system. Specifically, for the step reference input, it can provide a zero steady-state output tracking error. The controller design problem is solved by using the augmented state-space model as well as the static output feedback strategy. In addition, the stability of the closed-loop system is also discussed for the plant subject to bounded disturbances and modelling errors. Finally, simulation and experimental results are given to demonstrate the effectiveness of the proposed method.

In deregulated power system scenario coupled with smart grid technology, for networked load frequency control (LFC), an open communication structure, owing to low cost and flexibility, is preferred over dedicated networks in the feedback control loop for transmitting/receiving the data between the geographically displaced power system and the control center. In such a control scheme, closing the feedback loop through an open communication channel, in turn, introduces two additive time-varying delays of dissimilar characteristics in the feedback path. These delays degrade the performance of the closed-loop system, and exert a destabilizing effect on the overall system. In this paper, using Lyapunov-Krasovskii functional approach, a less conservative stability criterion is presented to ascertain delay-dependent stability of such network-controlled LFC systems with two additive time-varying delays in the feedback path in the presence of uncertain load disturbance conditions. Unlike the existing resul...

Networked Control Systems (NCSs) affected with packet dropouts and scheduling are considered. The undesirable effects of packet dropouts and scheduling, such as instability or deteriorated performance, are addressed by application of a protocol and controller co-design method. The used method exploits Model Predictive Control (MPC) framework and the flexible NCS architecture which allows for distributed computation. Uniform Global Asymptotic Stability (UGAS) is established by assuming a finite bound on the number of consecutive packet dropouts and appropriate modifications to often adopted MPC stability-related assumptions. Two approaches that demonstrate UGAS are provided. The proof of one approach consists of finding an appropriate Lyapunov candidate function, while the other uses a cascade stability idea.

Continual advances in information and communication technologies (ICT) are revolutionizing virtual education and bringing new tools on the market that provide virtual solutions to a range of problems. Nevertheless, nonvirtual experimentation using computer-aided control system design tools is still fundamental for future engineers. This paper describes a control course laboratory element, which is designed to teach electronic control engineering, in which students use a networked control system to steer and drive an electric car prototype. Multidisciplinary in nature, this laboratory allows students to take advantage of their previous academic training, as they model the plant from an open-loop test and contrast the simulated behavior with experimental results obtained on the prototype. A goal in this work was that students, across multiple engineering disciplines, should be able to integrate the knowledge acquired throughout their degree studies. An evaluation of students' grades, and their perception of the course, was conducted; this confirmed the educational benefits of the approach.

In order to deal with the networked control system (NCS) under random packet loss and uncertainties, an improved model predictive tracking control is provided in this paper. In the proposed control strategy, a novel state space model is introduced, where, unlike the conventional state space models, the tracking error and the state variables are combined and optimized together. Based on the improved state space model, more design degrees can be provided and better control performance can be acquired. A classical angular positioning system with uncertainties and a NCS with packet loss are introduced to illustrate the effectiveness of the proposed model predictive tracking control strategy, at the same time, the conventional model predictive control (MPC) approach is introduced as comparisons.

This paper is concerned with the event-triggered static output feedback control of networked control systems. The event-triggered mechanism is represented by a time-delay model and some latest techniques are employed to deal with the induced time-delay. Furthermore, a novel strategy is developed to eliminate the coupling among control gain, input matrix and output matrix. With these techniques, a new sufficient condition for system stability is established in the framework of linear matrix inequalities. The effectiveness of the proposed method is shown by two numerical examples.

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.

To improve the self-adapting ability and real-time performance of client/server based networked manufacturing system (NMS), this paper introduces the universal plug and play (UPnP), an intelligent network middleware, into networked manufacturing area, and proposes an embedded self-adapting network framework and related service methods. Referring to small world model and scale-free principles, a complex network model oriented to digital manufacturing is set up. Based on the model, an improved entropy vector projection algorithm is proposed to evaluate the network complexity and reveal the evolution regulars. Then, the self-adapting services for NMS are performed by UPnP service-calling and inter-process communication methods. Finally, the case studies and industrial field experiments verify the effectiveness of the proposed service framework.

We investigate the analysis and design of a control strategy for nonlinear systems under Denial-of-Service attacks. Based on an ISS-Lyapunov function analysis, we provide a characterization of the maximal percentage of time that feedback information can be lost without resulting in instability of the system. Motivated by the presence of a digital channel we consider event-based controllers for which a minimal inter-sampling time is explicitly characterized. (C) 2016 Elsevier B.V. All rights reserved.

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.

We consider the problem of resilient control of networked control system (NCS) under denial-of-service (DoS) attack via a unified game approach. The DoS attacks lead to extra constraints in the NCS, where the packets may be jammed by a malicious adversary. Considering the attack-induced packet dropout, optimal control strategies with multitasking and central-tasking structures are developed using game theory in the delta domain, respectively. Based on the optimal control structures, we propose optimality criteria and algorithms for both cyber defenders and DoS attackers. Both simulation and experimental results are provided to illustrate the effectiveness of the proposed design procedure.