Sampled-data Event-triggered Control Research Articles

Event-triggered control of systems with sector-bounded nonlinearities and intermittent packet transmissions

The problem of event-triggered sampled-data control of nonlinear systems with sector-bounded nonlinearities is considered. We assume that sensors transmit their measurements to the controller over a communication channel, where the success of transmissions is defined by an i.i.d. Bernoulli process. For the analysis of the closed-loop system stability, we use the Lyapunov–Krasovskii technique. As a result, we obtain stability conditions in terms of linear matrix inequalities (LMIs), which can be used to design the appropriate triggering parameters. A global strictly positive minimum inter-event time is guaranteed to exist by design with the proposed triggering condition. A numerical example demonstrates the efficiency of the event-triggered approach in reducing the number of transmissions compared to periodic sampling, where the period is the enforced minimum time in the event-triggering condition.

Output synchronization of reaction–diffusion neural networks under random packet losses via event-triggered sampled–data control

For space-varying reaction–diffusion neural networks (RDNNs), this article mainly studies the output synchronization via an event-triggered sampled-data (ETSD) control under spatially point measurements (SPMs) with random packet losses. To reduce the communication burden, an ETSD control scheme is adopted to decrease the unnecessary SD and the update frequency of the controller. Meanwhile, the problem of random packet losses in the communication channels from controller to actuator is considered. Some synchronization criteria based on spatial linear matrix inequalities (SLMIs) are established through an ETSD controller under SPMs with random packet losses to guarantee the mean square exponential stability of synchronization error system with drive and response dynamics via utilizing inequality techniques and Lyapunov functional. Furthermore, we express SLMIs as LMIs for solving the ETSD control design problem for output synchronization of space-varying RDNNs. Finally, the effectiveness of the proposed method is demonstrated by one numerical example.

Event-triggered control for nonlinear systems with impulse effects

This paper studies the exponential stability of nonlinear systems involving impulse effects based on event-triggered control, where the impulsive sequence is generated by some well-designed event conditions. On one hand, from the impulsive disturbance point of view, some sufficient conditions are derived based on event-triggered sampled-data control with the help of linear matrix inequalities (LMIs) method, where the control effects of sampled-data control and negative effects of impulses are fully considered. On the other hand, from the impulsive control point of view, some LMI-based conditions are presented based on event-triggered hybrid control, i.e., event-triggered sampled-data control and impulsive control, where a class of forced impulses is introduced to reduce the conservatism of the control strategy. The control gains of sampled-data control and impulsive control can be easily designed via our designed LMI conditions. Moreover, the Zeno behaviour can be excluded in our results. Finally, two numerical examples are presented to illustrate the validity of our control strategies.

Sampled-data event-triggered control with application to quadcopter formations

This paper proposes a novel distributed formation controller for general linear multi-agent systems with application to multiple quadcopters. First, a new locally computable state-estimate-based event-triggering communication condition is proposed for each agent. Then, the formation tracking problem is formulated as a stability analysis, controller gain and event-generator gain design problem of the closed-loop formation error dynamics. Sufficient conditions that guarantee the co-existence of a valid formation controller and an event-triggered communication mechanism are derived using a Lyapunov-based method and linear matrix inequality techniques. In addition, equivalent low (agent-sized) dimensional sufficient conditions are obtained to reduce the computational complexity. For the simulation conditions used in this research, the proposed estimate-based event-triggered communication mechanism generates less data communication instants when compared with traditional state-error-based mechanisms while still achieving similar control performance.

Research on Master-Slave Synchronization of Time-Delay Lur’e Systems Based on Event Triggering

The master-slave synchronization of chaotic Lur’e systems with time-varying delays was investigated based on the event-triggered sampled-data control. First, the transmission time delays contained in the systems were considered, and the system time delay model was constructed. Then, the Lyapunov-Krasovskii functionals with triple integrals were constructed, the Wirtinger integral inequality and the convex combination technique were combined to estimate the derivatives of the Lyapunov-Krasovskii functionals, and the sufficient conditions for the master-slave synchronization of the chaotic system were given. Application of the proposed event-triggered mechanism to master-slave synchronization can effectively reduce the sampled data transmission, alleviate the pressure on the network bandwidth, and improve the utilization rate of the network bandwidth. Finally, the numerical simulation of the time-delay Chua’s circuit verifies the effectiveness of the proposed synchronization criterion.

Leader-following consensus of multi-agent systems via novel sampled-data event-triggered control

A novel sampled-data event-triggered control (SDETC) for multi-agent systems (MASs) is proposed in this study, which is a more general form with the advantages of more flexible triggering techniques such as LIoDT, EIoDT, LT described in Remark 2.1, 2.2 covering many existing cases [1, 2, 3, 4]. It eliminates the Zeno behavior based on itself structure without difficult proof in the triggering scheme and has the upper triggering interval easily, avoiding the problem that it is not easy to solve linear matrix inequalities (LMIs) if applying the existing method [5] due to the triggering instants in LMIs. The node-based triggering time instants {tsi} in SDETC and the non-node-based impulsive time instants {tk} are well integrated. Cyber attack is considered in the transmission of information in the controller with SDETC for MASs. Leader-following consensus conditions of MASs via the novel impulsive SDETC are constructed. Finally, numerical examples give verification of the proposed methods.

Adaptive Event-Triggered Synchronization of Reaction-Diffusion Neural Networks.

This article focuses on the design of an adaptive event-triggered sampled-data control (ETSDC) mechanism for synchronization of reaction-diffusion neural networks (RDNNs) with random time-varying delays. Different from the existing ETSDC schemes with predetermined constant thresholds, an adaptive ETSDC mechanism is proposed for RDNNs. The adaptive ETSDC mechanism can be promptly adaptively adjusted since the threshold function is based on the current sampled and latest transmitted signals. Thus, the adaptive ETSDC mechanism can effectively save communication resources for RDNNs. By taking the influence of uncertain factors, the random time-varying delays are considered, which belongs to two intervals in a probabilistic way. Then, by constructing an appropriate Lyapunov-Krasovskii functional (LKF), new synchronization criteria are derived for RDNNs. By solving a set of linear matrix inequalities (LMIs), the desired adaptive ETSDC gain is obtained. Finally, the merits of the adaptive ETSDC mechanism and the effectiveness of the proposed results are verified by one numerical example.

Reliable stability and stabilizability for complex-valued memristive neural networks with actuator failures and aperiodic event-triggered sampled-data control

This study addresses the stability and stabilizability problems for complex-valued memristive neural networks (CVMNNs) with actuator failures via reliable aperiodic event-triggered sampled-data control. Different from the traditional control methods with time-triggered mechanism, an aperiodic event-triggered sampled-data control scheme is first proposed for CVMNNs. Taking the influence of actuator failures into account, a reliable controller is designed. In comparison with the existing control approaches, the one here is not only more applicable but effective to save the communication resources for CVMNNs. Then, a new Lyapunov–Krasovskii functional (LKF) is introduced, which can fully capture the information of sampling and complex-valued activation functions. Based on the LKF and some new estimation techniques, novel stability and stabilizability criteria are established, and the desired reliable aperiodic event-triggered sampled-data controller gains are obtained simultaneously. Finally, numerical simulations are provided to verify the effectiveness of the obtained theoretical results.

Fuzzy Adaptive Event-Triggered Sampled-Data Control for Stabilization of T–S Fuzzy Memristive Neural Networks With Reaction–Diffusion Terms

This article focuses on the design of a fuzzy adaptive event-triggered sampled-data control (AETSDC) scheme for stabilization of Takagi-Sugeno (T-S) fuzzy memristive neural networks (MNNs) with reaction-diffusion terms (RDTs). Different from the existing T-S fuzzy MNNs, the reaction and diffusion phenomena are considered, which make the presented model more applicable. A fuzzy AETSDC scheme is proposed for the first time, in which different AETSDC mechanisms will be applied for different fuzzy rules. For each fuzzy rule, the corresponding AETSDC mechanism can be promptly adaptively adjusted based on the current and last sampled signals. So the fuzzy AETSDC scheme can effectively save the limited communication resources for the considered system. By introducing a suitable Lyapunov- Krasovskii functional, new stability and stabilization criteria are established for T-S fuzzy MNNs with RDTs. Meanwhile, the desired fuzzy AETSDC gains are obtained. Finally, simulation results are given to verify the superiority of the fuzzy AETSDC scheme and the effectiveness of the theoretical results.

Event-Triggered Sampled-Data Control: An Active Disturbance Rejection Approach

The problem of event-triggered sampled-data control for networked systems is considered in this article. A nonlinear continuous-time system with uncertainty and disturbance is introduced, for which an event-triggered control problem based on an active disturbance rejection control approach is formulated. We first present the framework of the closed-loop system in which the control signal is transmitted at each event instant while the output measurements are transmitted in real time. Based on this framework, an easy-to-implement event-triggering strategy that relies on the state observation generated by an extended state observer is proposed, so that the asymptotic boundedness of the observation error is obtained and the stability of the closed-loop system can be guaranteed. Then, with some mild restrictions on initial values of the observer and plant, the boundedness of observation error can be maintained at any time. Finally, we extend the obtained results to a more general case in which the transmission of the measurements and control inputs are determined by separate event-triggering strategies. The performance of the proposed method is verified through experimental results on a direct current motor loading platform.

Consensus of fractional-order multiagent system via sampled-data event-triggered control

This paper investigates the consensus of fractional-order multiagent systems via sampled-data event-triggered control. Firstly, an event-triggered algorithm is defined using sampled states. Thus, Zeno behaviors can be naturally avoided. Then, a distributed control protocol is proposed to ensure the consensus of fractional-order multiagent systems, where each agent updates its current state based on its neighbors’ states at event-triggered instants. Furthermore, the pinning control technology is taken into account to ensure all agents in multiagent systems reach the specified reference state. With the aid of linear matrix inequalities (LMI), some sufficient conditions are obtained to guarantee the consensus of fractional-order multiagent system. Finally, numerical simulations are presented to demonstrate the theoretical analysis.