An improved memory-event-triggered control for networked control systems

In this paper, the H_∞ control problem is investigated for a class of networked control systems with network-induced delay. A memory event-triggered scheme (METS) is proposed to reduce the redundant packet transmission in the network channel. Different from the normal event-triggered scheme (ETS), some recent released packets are stored at the event generator and controller sides, which are utilized for the first time to generate the triggered events and design the memory-based controller. The proposed METS has the following two merits. (1) The information of certain recent released signals are first utilized, which helps to improve the triggering instants at the crest or trough of the responses. (2) A state-dependent time-varying threshold parameter is designed, which can adjust the packet transmission rate according to the information of the state. Based on the proposed METS, a memory event-triggered controller is designed, the controller feedback gains and triggering parameters can be co-designed by solving a set of linear matrix inequalities. Finally, an example is given to illustrate the effectiveness of the proposed method.     

Event-triggered fault estimation and fault-tolerant control for networked control systems

This paper is concerned with the event-triggered fault estimation and fault-tolerant control for continuous-time dynamic systems subject to system fault and external disturbance under network environment. Firstly, based on the event-triggered sampling, a fault diagnosis observer is constructed to estimate both the system state and the system fault simultaneously, and a multi-objective constraint is established to guarantee the estimation accuracy. Based on the estimated system state and fault signal, a fault-tolerant controller is proposed to compensate the influence of occurred faults and maintain the system performance. The event-triggered scheme and the fault-tolerant controller are co-designed to guarantee the required performance of faulty system and reduce the consumption of communication resources. Finally, simulation results of an F-404 aircraft engine system are provided to demonstrate the effectiveness of the proposed method.     

Robust packet-based nonlinear fuzzy networked control systems

A class of networked nonlinear control systems with norm-bounded uncertainties is presented in this paper. The class is represented by Takagi–Sugeno (T-S) fuzzy models with packet processing. The network loop delay is considered either as known delay or random delay. For the former case, we develop conditions that guarantee the robust asymptotic stability and state-feedback stabilization with strict dissipativity and cast the results in linear matrix inequality (LMI) framework. Next employing a probabilistic-based delay partitioning method to deal with random delay, we establish novel LMI criteria for strict dissipative stability analysis and feedback synthesis. The efficacy of the ensuing techniques is demonstrated by numerical solution of typical examples and Mont Carlo simulation.     

Optimal tracking performance for networked control systems with quantization

This paper investigates the optimal tracking performance of the multiple-input multiple-output (MIMO) discrete-time networked control systems (NCSs) considering the quantization of communication channel. The tracking performance is adopted for the H₂ square error criterion. The optimal tracking performance expression is obtained by using the co-prime factorization, the partial factorization, the inner–outer factorization and the spectral decomposition methods. Moreover, the paper also includes the exploration of the optimal tracking performance with input power constraint. The obtained results have demonstrated that the optimal tracking performance is influenced by the non-minimum phase zeros, unstable poles and their directions, the reference signal and the quantization interval. Moreover the theoretical results have also been proven using a number of different examples.     

Cooperative surrounding control with collision avoidance for networked Lagrangian systems

This paper investigates the cooperative surrounding control problem for networked multi-agent systems with nonlinear Lagrangian dynamics. With the consideration of the target with constant and time-varying velocity, two cooperative surrounding control algorithms with collision avoidance are proposed, in which possible collision among agents is prevented so as to achieve a more reliable and safer performance. For the case when the target has a constant velocity, a velocity observer is designed firstly for each agent. Secondly, to handle the nonlinear dynamics and avoid collisions, the neural networks and potential functions are used for the controller design. Then, the cooperative surrounding control algorithm is proposed such that all the agents surround the target with the desired relative positions. For the case when the target has a time-varying velocity, the velocity observer is designed under the assumption that the target’s partial acceleration is known for each agent. Then, the cooperative surrounding control algorithm is proposed such that the surrounding error between the target and each agent is bounded. The main difference between these two algorithms is that the former can ensure the collision avoidance among target and agents, while the latter can do so only among agents because the target’s velocity is time-varying. The Lyapunov theory is used to prove the stability of the cooperative surrounding control algorithms. The simulation illustrates the effectiveness of the theoretical results.     

Input-output finite-time stability for networked control systems with memory event-triggered scheme

This paper has investigated the input-output finite time stability (IO-FTS) for a class of networked control systems (NCSs) with network-induced delay. To reduce the frequents of packets transmission, a novel memory event-triggered scheme (METS) has been proposed. Different from existing event-triggered schemes, the proposed METS can make use of certain released packets to generate new event. By this way, the event generator can do more precise decision and better control performance can be expected. By using a Lyapunov functional method, sufficient condition for the IO-FTS of NCSs has been derived. Then a co-design method is proposed to obtain the memory feedback gains and parameters of the METS. Finally, a simulation example is carried out and the effectiveness of the designed METS is validated. The IO-FTS of NCSs with solved memory feedback gains is also confirmed.     

Evaluation of fault diagnosability for networked control systems subject to missing measurements

The evaluation of fault diagnosability for networked control systems subject to missing measurements is addressed in this paper. In particular, the missing probability is assumed to be affected by norm-bounded uncertainties. By considering noise and missing measurements, the quantitative diagnosability problem is investigated via the principle of weight. To quantify the effect of uncertain missing probabilities, an interval criterion is presented and uncertainty ratio is defined. Furthermore, a novel method is proposed to alleviate the computation task of evaluating fault diagnosability. The effectiveness of the proposed method is verified by a numerical example.     

Event-based control for networked T-S fuzzy cascade control systems with quantization and cyber attacks

This paper investigates the event-based control for networked T-S fuzzy cascade control systems with quantization and cyber attacks. In order to solve the problem of limited communication resources, an event-triggered scheme and a quantization mechanism are adopted, which can effectively reduce the burden of communication and save the network resources of the system. By considering the influence of cyber attacks, a newly quantized T-S fuzzy model for networked cascade control systems (NCCSs) under the event-triggered scheme is established. By using the Lyapunov stability theory, sufficient conditions guaranteeing the asymptotical stability of networked T-S fuzzy cascade control systems are obtained. In addition, the controller gains are derived by solving a set of linear matrix inequalities. Finally, a numerical example is presented to verify the validity of the proposed method.     

Quantized control of event-triggered networked systems with time-varying delays

The paper is a study of quantized control for stochastic Markov jump systems with interval time-varying delays and bounded system noise under event-triggered mechanism. A new scheme of Lyapunov–Krasovskii functional which contains the quadratic terms and integral terms is presented. Then quadratic convex technology, the theory of stochastic switching system, and logarithmic quantizer are applied to this paper. The design of quantized controller is obtained with those methodologies. Different from previous results, our derivation applies the idea of second-order convex combination. The conservatism of stability criteria for systems is reduced by using this method. A numerical example under different conditions is given to demonstrate the effectiveness and validity of the new design techniques.     

Improved approaches on adaptive event-triggered output feedback control of networked control systems

This paper studies the static output-feedback control in a class of networked control systems. Different from the existing results, the transmission of control signals is based on a novel adaptive event-triggered scheme, where the adaptive thresholds depend on the dynamic error of the system rather than predetermined constants as the traditional ones. The amount of the releasing data is regulated by the adaptive thresholds that play an essential role in decision of whether releasing the sampled data or not. Through fully using the information on network-induced delay and introducing two adjusting parameters, an augmented Lyapunov–Krasovskii (L–K) functional is constructed. Especially, some novel Wirtinger-based integral inequalities are utilized to reconsider those previously ignored information, which can help reduce the conservatism. Furthermore, a novel constructive method is developed to obtain the controller gain by solving the achieved linear matrix inequalities (LMIs). Finally, three numerical examples are given to illustrate the efficiency of the presented results.     

Resilient sampled-data control design for singular networked systems with random missing data

This paper proposes an active resilient control strategy for singular networked control systems with external disturbances and missing data scenario based on sampled-data scheme. To characterize the missing data scenario, a stochastic variable satisfying Bernoulli distributed white sequence is introduced. Based on this scenario, in this paper, two different models are proposed. For both the models, by using Lyapunov–Krasovskii functional approach, which fully uses the available information about the actual sampling pattern, some sufficient conditions in terms of linear matrix inequalities (LMIs) are separately obtained to guarantee that the resulting closed-loop system is admissible and strictly dissipative with a prescribed performance index. In particular, Jensen’s and Wirtinger based integral inequalities are employed to simplify the integral terms which appeared in the derivation of stabilization results. Then, if the obtained LMIs are feasible, the corresponding parameters of the designed resilient sampled-data controller are determined. Finally, two numerical examples are presented to demonstrate the effectiveness of the proposed control design technique.     

Event-triggered fault estimation and sliding mode fault-tolerant control for a class of nonlinear networked control systems

This paper is concerned with integrated event-triggered fault estimation (FE) and sliding mode fault-tolerant control (FTC) for a class of discrete-time Lipschtiz nonlinear networked control systems (NCSs) subject to actuator fault and disturbance. First, an event-triggered fault/state observer is designed to estimate the system state and actuator fault simultaneously. And then, a discrete-time sliding surface is constructed in state-estimation space. By the use of a reformulated Lipschitz property and delay system analysis method, the sliding mode dynamics and state/fault error dynamics are converted into a unified linear parameter varying (LPV) networked system model by taking into account the event-triggered scheme, actuator fault, external disturbance and network-induced delay. Based on this model and with the aid of Lyapunov–Krasovskii functional method, a delay-dependent sufficient condition is derived to guarantee the stability of the resulting closed-loop system with prescribed H_∞ performance. Furthermore, an observed-based sliding mode FTC law is synthesized to make sure the reachability of the sliding surface. Finally, simulation results are conducted to verify the effectiveness of the proposed method.     

Robust distributed tracking control for linear multi-agent systems based on distributed intermediate estimator

This paper considers the distributed tracking control problem for linear multi-agent systems with disturbances and a leader whose control input is nonzero and not available to any follower. Based on the relative output measurements of neighboring agents, a novel distributed observer-based tracking protocol is proposed, where the distributed intermediate estimators are constructed to estimate the leader’s unknown control input and the states of the tracking error system simultaneously, then a distributed tracking protocol is designed based on the derived estimates. It is proved that the states of the tracking error system are uniformly ultimately bounded and an explicit tracking error bound is obtained. A simulation example of aircrafts verifies the effectiveness of the proposed method.     

Security-based resilient event-triggered control of networked control systems under denial of service attacks

This paper is concerned with the security control problem of the networked control system (NCSs) subjected to denial of service (DoS) attacks. In order to guarantee the security performance, this paper treats the influence of packet dropouts due to DoS attacks as a uncertainty of triggering condition. Firstly, a novel resilient triggering strategy by considering the uncertainty of triggering condition caused by DoS attacks is proposed. Secondly, the event-based security controller under the resilient triggering strategy is designed while the DoS-based security performance is preserved. At last, the simulation results show that the proposed resilient triggering strategy is resilient to DoS attacks while guaranteing the security performance.     

Event-based dynamic output-feedback controller design for networked control systems with sensor and actuator saturations

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.     

Event-triggered nonlinear filtering for networked systems with correlated noises

This paper focuses on the filtering problem for nonlinear networked systems with event-triggered data transmission and correlated noises. An event-triggered data transmission mechanism is introduced to reduce excessive measurements transmitted over a bandwidth-constrained network. Considering that process noise and measurement noise are one-step cross-correlated, an UKF-based filtering algorithm which depends on correlation parameter and trigger threshold is presented. Then sufficient conditions are established to ensure stability of the designed filter, where a critical value of the correlation parameter exists. Finally, the effectiveness of the proposed filtering algorithm is demonstrated by comparative simulations.     

Improving the performance of networked control systems with time delay and data dropouts based on fuzzy model predictive control

This paper proposes a fuzzy model predictive control (FMPC) combined with the modified Smith predictor for networked control systems (NCSs). The network delays and data dropouts are problems, which greatly reduce the controller performance. For the proposed controller, the model of the controlled system is identified on-line using the Takagi – Sugeno (T-S) fuzzy models based on the Lyapunov function. There are two internal loops in the proposed structure. The first is the loop around the FMPC, which predicts the future outputs. The other is the loop around the plant to give the error between the system model and the actual plant. The proposed controller is designed for controlling a DC servo system through a wireless network to improve the system response. The practical results based on MATLAB/SIMULINK are established. The practical results are indicated that the proposed controller is able to respond the networked time delay and data dropouts compared to other controllers.     

Towards quantifying the impact of randomly occurred attacks on a class of networked control systems

In this paper, the impacts from both cyber and physical attacks are analyzed for a class of networked control systems via a delta operator approach. A comprehensive attack model involving randomly occurred deception attack, denial-of-service attack and physical attack is established. The multi-tasking optimal control strategy is developed in the delta-domain such that the individual cost function for each player is minimized. For quantifying the impacts from attacks, an ?-Nash equilibrium is employed to describe the performance degradation. An explicit upper bound for the ?-Nash equilibrium is provided such that the maximum performance-loss induced by the considered all-around attacks is estimated. Some convex optimization algorithms are provided to compute an upper bound of the ?-Nash equilibrium. Finally, a numerical example is presented to illustrate the validity of the design scheme.     

Nonuniform sampling Kalman filter for networked systems with Markovian packets dropout

This paper focuses on a state estimation problem on networked systems with Markovian packets dropout. An event-based nonuniform sampling scheme is applied in intelligent samplers to save resources of the samplers and networks. Another sampling scheme combined with time-trigger and event-trigger is applied in a Kalman filter to detect the packets dropout. A delta operator Kalman filter is designed for the nonuniform sampling networked system. Two sufficient conditions of peak covariance stability and usual covariance stability are given to guarantee convergence of the delta operator Kalman filter. Numerical examples are shown to illustrate effectiveness of the developed techniques.