Event-triggered Sampling Control Research Articles

Dynamic output feedback control of switched systems: A dynamic event-triggered sampling control scheme

A dynamic event-triggered sampling scheme for dynamic output feedback control for a class of switched systems is proposed, where the triggering mechanism can exclude the Zeno phenomenon even if the state of the switched systems is within the output kernel space, and subsystems of the resulting closed-loop switched systems are not necessarily required to be stable. The proposed method can guarantee the Zeno-freeness property and global uniform exponential stability of the origin simultaneously under the impacts of triggering asynchronism and sampling errors. Moreover, sufficient conditions on the globally exponential stability are also given. Finally, the effectiveness of the proposed scheme is illustrated by a numerical example.

Dissipative Synchronization of Semi-Markov Jump Complex Dynamical Networks via Adaptive Event-Triggered Sampling Control Scheme

This article investigates the dissipative synchronization of complex dynamical networks (CDNs) with semi-Markov switching topological structures. First, by introducing a semi-Markov process, the model we investigated is more practical and stands for an extension of the Markov jump CDNs that have been widely studied. Second, an adaptive event-triggered sampling controller is newly proposed for semi-Markov jump CDNs, unlike the periodic event-triggered control scheme, the adaptive event-triggered sampling control strategy can further reduce the controller’s update frequency by adaptively adjusting its threshold. Moreover, with the help of a novel two-sided looped-functional and some advanced inequality techniques, the conservatism of the obtained result is greatly reduced. A sufficient synchronization condition that ensures the stochastic stability of the error system is established. Finally, to show the validity and superiority of the proposed method, several examples including some comparisons and applications are given in the simulation part.

Event-triggered stochastic consensus for networked Lagrangian systems with semi-Markov switching topologies and communication delays

In this paper, the event-triggered stochastic consensus for networked Lagrangian systems with semi-Markov switching topologies and communication delays is considered. An event-triggered sampling control strategy is used to design the distributed stochastic consensus scheme of networked Lagrangian systems for two cases with leader and leaderless. Two delay-dependent consensus criteria are derived in the sense of mean square by use of a suitable Lyapunov-Krasovskii functional and the stochastic delayed Halanay inequality, respectively. A key feature of the developed event-triggered consensus algorithm is to introduce a suitable adjustment parameter on consensus control gains characterizing the effect of both semi-Markov switching topology and communication delay. Finally, a numerical example of four manipulators with two links is presented to illustrate the effectiveness of the developed event-triggered methodology.

Event-Based Sampled-Data Average Consensus

This study addresses one of the most essential distributed control problems in multiagent systems, called the average consensus issue, using a new event-triggered sampling control perspective. Although the continuous-time sampling for average consensus has provided good results currently, a systematic investigation into the continuous-time agent dynamics with sampled-data control inputs under an event-triggered mechanism is critically lacking. The problem considered in this paper can be formulated into an average consensus problem of hybrid systems. The method considers three types of control schemes, among which periodic sampling is integrant. The first scheme is a classical sampling controller reinvestigated through a lemma. The second scheme realizes aperiodic control update as well as periodic communication, while the third scheme achieves both aspects aperiodically. Corresponding sufficient conditions of the aforementioned three schemes are derived such that the asymptotic stability of systems is ensured by using algebraic graph theory, matrix analysis, and Lyapunov theory. The constraints for the allowed sampling period, event parameter, and maximum eigenvalue of graph Laplacian are explicitly derived. Moreover, the potential Zeno behavior of agents due to the sampling control theory is avoided. Thus, a digitally implementable technique is provided. Finally, some numerical examples are provided to verify the effectiveness of the proposed theoretical analysis.

Fault-Tolerant Attitude Stabilization for Spacecraft With Low-Frequency Actuator Updates: An Integral-Type Event-Triggered Approach

This article investigates the attitude stabilization control problem with low-frequency communication to actuators in the framework of sampled-data control. A novel event-triggered sampling control policy is proposed by employing an integral-type triggering function where the determination of all sampling times is by judging the properties of this function including the integration of measurement errors. Using the Lyapunov-based approach, we show that the stability of the closed-loop system can be guaranteed in the presence of external disturbance, inertia uncertainty, and actuator fault. Compared with conventional attitude control policies, the proposed algorithm significantly reduces the data-rate requirement in updating the actuator while providing high reliability and accurate performance for attitude stabilization. Compared with the traditional event-triggered sampling, the proposed policy is no longer by judging the instantaneous state of measurement errors, which reduces the sampling frequency and does not increase the computational burden. Numerical simulations are conducted to show a decent performance of the algorithm.

Pinning Event-Triggered Sampling Control for Synchronization of T–S Fuzzy Complex Networks With Partial and Discrete-Time Couplings

This paper focuses on the synchronization problem of Takagi-Sugeno (T-S) fuzzy complex networks with partial and discrete-time couplings via event-triggered sampling control. Different from traditional control methods, a more general and practical event-triggered communication scheme with nonuniform sampling is newly designed for T-S fuzzy complex networks. Then, a Lyapunov-Krasovskii functional (LKF) with a novel input-delay-product-type (IDPT) term is presented. The IDPT term can fully capture the information of the nonlinear functions and the actual sampling pattern. Based on the new IDPT LKF, less conservative synchronization criteria are derived. Meanwhile, by solving a set of linear matrix inequalities, the desired pinning control gains are precisely obtained. Simulation examples are provided to illustrate the effectiveness and superiorities of the proposed results.

Periodic Event-Triggered Sampling and Dual-Rate Control for a Wireless Networked Control System With Applications to UAVs

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

Stabilization of Switched Linear Neutral Systems: An Event-Triggered Sampling Control Scheme

Event-triggered control is an effective control strategy, capable of reducing the amount of communications and retaining a satisfactory closed-loop performance. In this paper, we aim at proposing an event-triggered sampling mechanism and studying observer-based output feedback control for switched linear neutral systems with mixed time-varying delays. Different from the conventional event-triggered control strategies, our proposed one transmits not only the state but also the switching information to the controller, which is advantageous in applications where the measured outputs and the switching information have to be transmitted over a communication network. Moreover, asynchronous switchings may be caused between the subsystems and their matched subcontrollers under the proposed sampling mechanism, which increases difficulties in analyzing stability. We develop a sufficient condition, under which the proposed control scheme guarantees globally the exponential stability of the closed-loop system meanwhile taking into account asynchronous switchings. Finally, an illustrative example is given to show the effectiveness of the proposed method.

Event-triggered sampling and fault-tolerant control co-design based on fault diagnosis observer

A co-design scheme of event-triggered sampling mechanism and active fault tolerant control (FTC) is developed. Firstly, a fault diagnosis observer is designed to estimate both the fault and the state simultaneously by using the event-triggered sampled output. Some H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> constraints between the estimation errors and the event-triggered sampling mechanism are established to ensure the estimation accuracy. Then, based on the constraints and the obtained fault information, an event-triggered detector and a static fault tolerant controller are co-designed to guarantee the stability of the faulty system and to reduce the sensor communication cost. Furthermore, the problem of the event detector and dynamic FTC co-design is also investigated. Simulation results of an unstable batch reactor are finally provided to illustrate the effectiveness of the proposed method.

Event-triggered sampling control for exponential synchronization of chaotic Lur’e systems with time-varying communication delays

This paper investigates the exponential synchronization of chaotic Lur’e systems (CLSs) with time-varying communication delays through event-triggered sampling control. Specially, first, a discrete event-triggered sampling control scheme, which only sends necessary sampling signal through the network, is designed for CLSs. By using this controller, the number of control updates could greatly reduce. Second, by getting utmost out of the usable information on the actual sampling pattern, some new sawtooth structure terms are introduced in the constructed Lyapunov–Krasovskii functional (LKF). It is worth mentioning that, different from some existing results to restrict the LKF to be positive define on the whole sampling intervals, the LKF is positive definite only needing at sampling times thanks to the use of the new inequality in Lemma 1. Third, less conservative synchronization criteria are established and the desired control gain matrix is obtained. Finally, two Chua’s circuit numerical simulations are presented to validate the feasibility and effectiveness of the theoretical results.

Event-triggered sampling control for stability and stabilization of memristive neural networks with communication delays

This paper investigates the global asymptotic stability and stabilization of memristive neural networks (MNNs) with communication delays via event-triggered sampling control. First, based on the novel approach in Lemma 1, the concerned MNNs are converted into traditional neural networks with uncertain parameters. Next, a discrete event-triggered sampling control scheme, which only needs supervision of the system state at discrete instants, is designed for MNNs for the first time. Thanks to this controller, the number of control updates could greatly reduce. Then, by getting utmost out of the usable information on the actual sampling pattern, a newly augmented Lyapunov-Krasovskii functional (LKF) is constructed to formulate stability and stabilization criteria. It should be mentioned that the LKF is positive definite only at endpoints of each subinterval of the holding intervals but not necessarily positive definite inside the holding intervals. Finally, the feasibility and effectiveness of the proposed results are tested by two numerical examples.

Consensus analysis of multiagent systems with second-order nonlinear dynamics and general directed topology: An event-triggered scheme

Event-triggered sampling control is motivated by the application of embedded microprocessors equipped in the agents with limited computation and storage resources. This paper studies the global consensus in second-order multi-agent systems with the inherent nonlinear dynamics on general directed networks using decentralized event-triggered strategy. For each agent, only utilizing local and current sampling data, the update of controllers is event-based and only triggered at their own event times. A high-performance sampling event that only needs neighbors’ states at their own discrete time instants is presented. Furthermore, we introduce two kinds of general algebraic connectivity for strongly connected networks and strongly connected components of directed networks containing a spanning tree to describe the system's ability to reach consensus. A detailed theoretical analysis on consensus is performed and two criteria are derived by the virtues of algebraic graph theory, matrix theory, and Lyapunov control approach. It is shown that the continuous communication between neighboring agents can be avoided and the Zeno-behavior of triggered time sequence is excluded during the system's whole working process. In addition, numerical simulation is given to illustrate the effectiveness of the theoretical results.

Event-triggered consensus in nonlinear multi-agent systems with nonlinear dynamics and directed network topology

The event-triggered sampling control scheme is motivated by applications of embedded microprocessors with limited computation and storage resources. This paper proposes a novel framework for consensus of multiagent systems with inherent nonlinear dynamics in general directed networks by a distributed event-triggered control mechanism. A kind of high-performance event which effectively avoids continuous communications among agents is designed to analytically determine when an agent should sample its current state. Two kinds of general algebraic connectivity are introduced to respectively investigate the global consensus in strongly connected networks and a class of networks containing directed spanning trees. Sufficient conditions are derived to reach a global consensus based on algebraic graph, matrix theory, and Lyapunov control approach. A numerical example is presented to demonstrate the correctness of the theoretical results.