Output-Feedback-Based Event-Triggered Control of Multi-Agent Systems Without Continuous Inter-Agent Communication

We propose two distributed dynamic triggering laws to solve the consensus problem for multi-agent systems with event-triggered control. Compared with existing triggering laws, the proposed triggering laws involve internal dynamic variables which play an essential role to guarantee that the triggering time sequence does not exhibit Zeno behavior. Some existing triggering laws are special cases of our dynamic triggering laws. Under the condition that the underlying graph is undirected and connected, it is proven that the proposed dynamic triggering laws together with the event-triggered control make the state of each agent converges exponentially to the average of the agents' initial states. Numerical simulations illustrate the effectiveness of the theoretical results and show that the dynamic triggering laws lead to reduction of actuation updates and inter-agent communications.

This paper studies the consensus problem for multi-agent systems with quantised information communication via event-triggered control. First, the asynchronous event-triggered control for multi-agent systems is considered based on distributed uniform-quantised protocols. It is shown that practical consensus among agents is guaranteed and occurrence of Zeno behaviour is prevented under the designed event-triggering mechanisms. Second, under the proposed protocols using logarithmic quantised information, both synchronous and asynchronous event-triggered control algorithms are given to solve the practical consensus problem. Meanwhile, Zeno behaviour of the closed-loop systems can be excluded under the proposed event-triggered algorithms. Finally, numerical simulations are given to illustrate the effectiveness of the derived results.

Event-triggered control for multi-agent systems with randomly occurring nonlinear dynamics and time-varying delay

A decentralized event-triggered approach is developed for leader–follower systems with time-invariant and time-varying network topologies in the absence of full-state feedback. Continuous interagent communication is eliminated by communicating information only during events. At the event times, an observer communicates with the neighboring agents to obtain update information. During the interevent intervals, an open-loop estimate is used as a substitute for local feedback. The advantages of our novel approach are that: 1) the amount of communication required can be reduced and determining the event times requires no interagent communication, with the event-triggered condition designed using stability analysis so that bounded consensus is guaranteed; 2) bounded state consensus can be achieved without receiving full-state information from the followers; and 3) the switching sequence of the time-varying network topologies can be arbitrary, since a switching controller is developed based on the common-Lyapunov-function approach to ensure state consensus. Intermittent feedback is present and the dynamics of the time-varying network topologies are discrete, which together prove that Zeno behavior never occurs. The stability of the closed loop is analyzed to guarantee bounded convergence for the designed control methodologies. The results of simulations are presented that demonstrate the efficacy of our novel controllers.

A survey on recent advances in event-triggered communication and control

Multi-agent systems (MAS) refers to a system that is made of systems. This group of systems promises to be more efficient than single individual systems in terms of reliability and capabilities. This paper suggests, by event activated control approach the consensus problem of a distributed multi-agent network consisting of single integrator dynamics. The event condition and the consensus protocol are developed based on only local information. The event-activating conditions are only checked periodically to decide whether to refresh the information states of the agents or not. The event condition is obtained by conducting convergence analysis based on Lyapunov method. Simulation results are illustrated to show the correctness and realizability of the suggested consensus protocol.

In this paper, a neural network (NN)-based distributed cooperative identification strategy with event-triggered communication is studied for a group of coupled identical nonlinear systems. We develop a distributed cooperative learning law in the context of event-triggered communication, where an agent will transmit its NN weights to its neighbors only when its weight trigger error norm exceeds an exponentially decreasing threshold. It is proven that the estimated weights of all radial basis function NNs converge to a small neighborhood of their optimal values. Therefore, the unknown nonlinear function is approximated along the union of all the system trajectories. It is further proven that there exists a positive minimum interevent interval and Zeno behavior can be avoided. Finally, we give a simulation example to demonstrate these features.

This brief considers the leader-following consensus (consensus tracking) problem of multi-agent systems (MAS) with event-triggered communication. A novel hybrid event-triggering mechanism is proposed to reduce the burden of network transmission, and it is ensured that Zeno behavior does not occur. Besides, it is required that the control protocol is only updated at agent’s own triggering instant. Compared with the existing works, the main contribution is that the minimum inter-event time (MIET) can be pre-specified, which is important for physical implementation, and the control update frequency is also reduced. An example is given to verify the correctness of the proposed hybrid event-triggered control strategy.

In this article, we investigate the event-triggered containment control problem for a class of multiagent systems, where agents are described by higher-order linear dynamics subject to stochastic disturbances. In event-triggered control scenarios, the control action is updated when a specified error reaches a given threshold. Due to the existence of stochastic factors, the given threshold may be reached in an any short time interval, which makes it hard to avoid Zeno behavior. In view of this, we propose two novel event-triggered containment control schemes for the underlying multiagent systems with stochastic disturbances. Using the stochastic control theory, graph theory, and Lyapunov functional method, it is proven that the followers' states can almost surely converge to the convex hull spanned by the leaders’ states. It is noted that the continuous communications among agents are not required and each agent's inter-event intervals are lower-bounded by a positive constant. As such, the proposed control schemes are both practical and implementable. Finally, a numerical example is presented to illustrate the developed schemes’ effectiveness.

In this article, we investigate the event-triggered consensus problem for general linear multiagent systems with bounded communication network delay. To reduce the communication frequency, we propose some dynamic periodic event-triggering strategies, under which an auxiliary dynamic variable and a weighting parameter are introduced for each agent to build its event-triggering condition. Then, a distributed adaptive consensus protocol, which includes a time-varying coupling weight for each edge, is designed based on the proposed event-triggering strategies. With the well-designed updating laws of dynamic variables, coupling weights and weighting parameters, we can theoretically guarantee the consensus of the concerned multiagent systems. Our event-triggering strategies do not require agents to continuously verify the event-triggering conditions or read their neighbors’ real-time state information. Moreover, Zeno behavior is inherently excluded as the interevent intervals are bounded from below by one period in the periodic event-triggering framework. Two numerical examples are provided to verify the effectiveness of the proposed event-triggered consensus protocols.

The finite‐time consensus problem for leader‐following systems was evaluated under external disturbances and internal nonlinear dynamics. A model with nonlinear dynamics and external disturbances was proposed to make the systems more realistic. The event‐triggered pinning control strategy was used in second‐order multiagent systems to address the problem of the agents' continuous communication. A new event‐triggered control function was designed, and a finite‐time controller was constructed using an integral sliding‐mode algorithm. The systems can be proven to achieve consensus in the expected convergence time, which can be obtained using finite‐time and Lyapunov stability theories. Moreover, the Zeno behavior can be proven to avoid event‐triggered controllers. Finally, a numerical example was presented to illustrate the effectiveness and accuracy of the theoretical analysis.

A novel model predictive control- (MPC-) based trajectory tracking controller for mobile robot is proposed using the event-triggering mechanism, and the aim is to solve the problem that the MPC optimization problem requires a large amount of online computation and communication resources. This method includes two different event-triggering strategies, namely, the event-triggering based on threshold curve and the event-triggering based on threshold band. The selection of the triggering threshold is achieved by applying the statistical method to the historical data of the trajectory tracking of the mobile robot under the classic MPC method. Simulation and experimental tests illustrate that the proposed approach is able to significantly reduce the computation and communication burdens without affecting the control performance. Furthermore, the experimental results show that compared with the classic MPC-based tracking method, the proposed two event-triggering strategies can reduce 28.1% and 75.7% of the computation load and 0.886 s and 2.385 s communication time.

Distributed event-based consensus control of multi-agent system with matching nonlinear uncertainties

This study is on H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> output feedback control design for a class of discrete Markov jump systems with event-triggered scheme and quantizations. First, an event-triggered communication scheme is proposed. Second, a novel Markov jump time-delay system model with external disturbances is established, bearing in mind the influence of network delay. Next, we set two quantizers, one in the sensor-controller channel, and the other in the controller-actuator channel. As a result, the sufficient conditions are obtained to guarantee the stability and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control performance of the closed-loop system, and to present the output feedback controller design. Finally, an example is given to demonstrate the effectiveness of the proposed method.

Fully distributed observer-based tracking control for Lur’e systems with event-triggered communication