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.     

Reliable control for event-triggered singular Markov jump systems with partly unknown transition probabilities and actuator faults

In this paper, the problem of reliable controller design for event-triggered singular Markov jump systems with partly known transition probabilities, nonlinear perturbations and actuator faults is studied. To mitigate the burden of data transmissions over network, two event-triggered schemes with different triggering conditions are introduced. The switch law between the two event-triggered schemes is governed by a random variable with Bernoulli distribution. Taking nonlinear perturbations and actuator faults into account, the resulting closed-loop system is converted into a time-delay singular Markov jump system with partly known transition probabilities. Sufficient conditions of stochastically admissible for the resulting closed-loop system are obtained in terms of a group of linear matrix inequalities. The co-design of desirable reliable controller and weighting matrices of event-triggered schemes is presented. Finally, two numerical examples are given to show the effectiveness of the developed results.     

Distributed impulsive control for heterogeneous multi-agent systems based on event-triggered scheme

In this paper, the distributed impulsive control for heterogeneous multi-agent systems based on event-triggered approach is investigated. According to whether the information transfer of the dynamic compensator is continuous or not, two different kinds of impulsive controllers are designed, respectively. Based on these two kinds of controllers, the corresponding distributed event-triggered conditions are provided, which make the impulsive instants of all agents do not need occur simultaneously. Moreover, the lower bound of impulsive intervals can also be guaranteed for all the event-triggered conditions, which means that the control schemes given in this paper can avoid the Zeno-behavior successfully. Eventually, a simulation example is proposed to support the effectiveness of the results obtained in this paper.     

Leaderless consensus of multi-agent systems via an event-triggered strategy under stochastic sampling

This paper investigates mean square leaderless consensus of networked nonlinear multi-agent systems. An efficient distributed event-triggered mechanism based on stochastic sampling is introduced to reduce the communication cost and controller updates. The stochastic sampling interval randomly switches between two given values. Mean square consensus criteria for multi-agent systems with strongly connected networks or networks containing directed spanning trees are derived, respectively. Moreover, the case with a special event-triggered weighting matrix and the case without even-triggered strategies are also discussed. Finally, an example is given to verify the theoretical results.     

Networked load frequency control of multi-area uncertain power systems via adaptive event-triggered communication scheme

Load frequency control of power systems is a very important approach to keep stability and security. Unfortunately, the traditional load frequency control is not effective because of the introduction of communication networks in multi-area power systems. In order to overcome this difficulty, sampling-based load frequency control for multi-area power systems is studied via an event-triggered detector. Unlike published works, an adaptive law for event-triggered scheme is given. Since multi-area power systems with event-triggered scheme are hybrid systems, there are a lot of challenges for analysing load frequency control problem. Some lemmas and a new Lyapunov function are developed to overcome these challenges. The obtained stability and stabilization criteria can provide a tradeoff to balance the required communication resources and the desired control performance. Numerical examples verify effectiveness of the obtained results.     

Finite-time asynchronous filtering for switched linear systems with an event-triggered mechanism

This paper investigates the event-triggered finite-time H_∞ filtering for a class of continuous-time switched linear systems. Considering that the system may switch within an inter-event interval, the asynchronous problem is taken into account for the system and filter modes. By adopting the average dwell time (ADT) technique and multiple Lyapunov functions, new conditions are obtained to guarantee that the filtering error system is finite-time bounded with a prescribed disturbance attenuation performance. Further, the finite-time H_∞ filter together with event-triggered mechanism is co-designed for the switched linear systems. Finally, a numerical example is provided to demonstrate the effectiveness of the method proposed in this paper.     

Resilient event-triggered consensus control for nonlinear muti-agent systems with DoS attacks

The distributed event-triggered secure consensus control is discussed for multi-agent systems (MASs) subject to DoS attacks and controller gain variation. In order to reduce unnecessary network traffic in communication channel, a resilient distributed event-triggered scheme is adopted at each agent to decide whether the sampled signal should be transmitted or not. The event-triggered scheme in this paper can be applicable to MASs under denial-of-service (DoS) attacks. We assume the information of DoS attacks, such as the attack period and the consecutive attack duration, can be detected. Under the introduced communication scheme and the occurrence of DoS attacks, a new sufficient condition is achieved which can guarantee the security consensus performance of the established system model. Moreover, the explicit expressions of the triggering matrices and the controller gain are presented. Finally, simulation results are provided to verify the effectiveness of the obtained theoretical results.     

Dissipative observers for discrete-time nonlinear systems

This paper addresses the problem of designing a state observer for a class of nonlinear discrete-time systems using the dissipativity theory. We show that the dissipative observation methodology, originally proposed by one of the authors for continuous-time nonlinear systems, can be extended to the discrete-time case. For constructing a convergent observer, the methodology is applied to the nonlinear estimation error dynamics, which is decomposed into a discrete-time Linear Time-Invariant (LTI) subsystem in the forward loop, connected to a time-varying static nonlinearity in the feedback loop. In order to assure asymptotic stability of the closed-loop, complementary dissipativity conditions are imposed on each of the subsystems: (i) the static nonlinearity is required to be dissipative with respect to a quadratic supply rate, and (ii) the observer gains are designed such that the LTI system is dissipative with respect to a complementary supply rate. As in the continuous time framework, the proposed method includes as special cases, unifies and generalizes some observer design methods proposed previously in the literature. A great advantage of the Dissipative Observer Design Method proposed here is that it leads to Matrix Inequalities for the design of the observer gains, and these can be usually converted into Linear Matrix Inequalities (LMI’s). The results are illustrated using Chua’s Chaotic system.     

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.     

Subspace predictive control with the data-driven event-triggered law for linear time-invariant systems

In this paper, a subspace predictive control (SPC) method with a novel data-driven event-triggered law is proposed for linear time-invariant systems with unknown model parameters. Based on the conventional SPC method, the event-triggered law is introduced to substitute the typical receding horizon optimization, which reduces the data computation load of the traditional SPC method. The key parameters of the event-triggered law are derived by the Q-learning method via system data and the input-to-state stability of the system can be ensured with the designed event-triggered law. The simulation results illustrate the effect and merits of the proposed method with comparisons.     

Distributed event-triggered control co-design for large-scale systems via static output feedback

This work investigates the problem of distributed control for large-scale systems, in which a communication network is available to exchange information. To avoid the unnecessary communication, an event-triggered control (ETC) mechanism is introduced, in which the transmission occurs only when a certain event is triggered. Under the assumption that only the output signal is available, the static output feedback (SOF) is considered in this work. The aim of the co-design is to design an SOF controller and an ETC condition simultaneously such that the overall closed-loop system is stabilized with a certain level of performance. To this end, an event-triggering scheme based on output signals is proposed to determine when the event is triggered. Then the closed-loop system is modeled as a linear perturbed system. The distributed control co-design is formulated as a convex optimization problem with linear matrix inequalities (LMIs) constraints. Finally, a numerical example is presented to show the effectiveness of the proposed design method.     

Distributed adaptive event-triggered protocol for tracking control of leader-following multi-agent systems

A novel adaptive event-triggered control protocol is developed to investigate the tracking control problem of multi-agent systems with general linear dynamics. By introducing the event-triggered control strategy, each agent can decide when to transfer its state to its neighbors at its own triggering instants, which can greatly reduce communication burden of agents. It is shown that the “Zeno phenomenon” does not occur by verifying that there exists a positive lower bound on the inter-event time intervals of agents under the proposed adaptive event-triggered control algorithm. Finally, an example is provided to testify the effectiveness of the obtained theoretical results.     

Bounded average consensus for multi-agent systems with switching topologies by event-triggered persistent dwell time control

This paper is concerned with the consensus of multi-agent systems (MASs) with switching topologies. A norm-bounded event-trigger is designed where non-global information of the communication graph is involved. By directly employing the asynchronous event-triggered neighbor state information, a distributed persistent dwell time (PDT) based predictor-like consensus protocol is proposed. By the proposed scheme, the dynamics of local subsystems are allowed to be unstable during fast switching time intervals as well as the jump time instants, meanwhile, the bounded average consensus of overall MASs can be achieved. In addition, the Zeno-phenomena is naturally excluded. Numerical example is provided to demonstrate the effectiveness of the proposed method.     

Observer-based control for singular nonhomogeneous Markov jump systems with packet losses

This paper is concerned with the observer-based H_∞ control for a class of singular Markov jump systems over a finite-time interval, where the transition probability (TP) is time-varying and is limited to a convex hull. Due to the limited capacity of network medium, packet losses are presented in the underlying systems. Firstly, using a stochastic Lyapunov functional, a sufficient condition on singular stochastic H_∞ finite-time boundedness for the corresponding closed-loop error systems is provided. Subsequently, a linear matrix inequality (LMI) condition on the existence of the H_∞ observer-based controller is developed from a new perspective. Finally, three numerical examples are provided to illustrate the effectiveness of the proposed controller design method, wherein it is shown that the proposed method yields less conservative results than those in the literature.     

Distributed Kalman consensus filter with event-triggered communication: Formulation and stability analysis

This paper deals with the distributed estimation problem for networked sensing system with event-triggered communication schedules on both sensor-to-estimator channel and estimator-to-estimator channel. Firstly, an optimal event-triggered Kalman consensus filter (KCF) is derived by minimizing the mean squared error of each estimator based on the send-on-delta triggered protocol. Then, the suboptimal event-triggered KCF is proposed in order to reduce the computational complexity in covariance propagation. Moreover, the formal stability analysis of the estimation error is provided by using the Lyapunov-based approach. Finally, simulation results are presented to demonstrate the effectiveness of the proposed filter.     

Stabilization of switched linear singular systems with state reset

This paper investigates the stability and stabilization of switched linear singular systems with state reset at switching instants. Based on the dynamics decomposition of singular subsystems, a sufficient stability condition for the system with the given state reset is obtained. Then, the stabilization problem by state reset is investigated and an algorithm for computing the reset matrices is presented. The obtained results extend some previous works on both singular switched systems and reset control for normal switched systems. Finally, a numerical example is presented to illustrate the effectiveness of the proposed approach.     

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.     

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.     

Probabilistic fuzzy logic controller for uncertain nonlinear systems

This paper proposes a probabilistic fuzzy proportional - integral (PFPI) controller for controlling uncertain nonlinear systems. Firstly, the probabilistic fuzzy logic system (PFLS) improves the capability of the ordinary fuzzy logic system (FLS) to overcome various uncertainties in the controlled dynamical systems by integrating the probability method into the fuzzy logic system. Moreover, the input/output relationship for the proposed PFPI controller is derived. The resulting structure is equivalent to nonlinear PI controller and the equivalent gains for the proposed PFPI controller are a nonlinear function of input variables. These gains are changed as the input variables changed. The sufficient conditions for the proposed PFPI controller, which achieve the bounded-input bounded-output (BIBO) stability are obtained based on the small gain theorem. Finally, the obtained results indicate that the PFPI controller is able to reduce the effect of the system uncertainties compared with the fuzzy PI (FPI) controller.