Distributed impulsive control consensus for a class of unknown nonlinear multi-agent systems based on event-triggered scheme

In this study, we are concerned with the impulsive consensus control problem for a class of nonlinear multi-agent systems (MASs) which have unknown dynamics and directed communication topology. The neural networks (NNs) method is the first utilized to construct distributed event-triggered impulsive consensus protocol. In contrast to the existing impulsive consensus protocol, the consensus protocol proposed in this paper does not need the dynamics of agents, which enhances the system robustness, and realizes distributed event-triggered communication between agents, which can reduce unnecessary consumption of communication resources. Sufficient conditions are derived to ensure the consensus of the controlled MASs and the exclusion of Zeno-behavior. Finally, simulation examples are presented to illustrate the effectiveness of the proposed control protocol.     

Practical scaled consensus for nonlinear multiagent systems with input time delay via a new distributed integral-type event-triggered scheme

This paper studies scaled-based practical consensus issue for multiagent systems with input time delay by a fully continuous communication-free integral-type event-triggered scheme. By choosing the proper scales, scaled consensus can be induced to synchronization, bipartite consensus or cluster consensus. By defining a continuous communication-free measurement error for the integral-type event-triggered mechanism, the new integral-type event-triggered condition is proposed which can not only reduce the energy consumption but also prolong the interevent time. Then, with time domain analysis method, the distributed integral-type event-triggered control problem for nonlinear general multiagent systems involving input time delay is investigated and then the second-order counterpart, with a calculated upper-bound for time-delay. Moreover, it is concluded that with such event-triggered protocols, practical scaled consensus can be achieved without the exhibition of Zeno behavior. At last, simulations are shown to support the results.     

基于事件触发策略的多智能体系统的最优主-从一致性分析

研究了具有领导者的线性多智能体系统的主 从一致性问题.借助各智能体间的通讯拓扑所构成的无向图,提出一种基于事件触发的自适应动态规划方法,并使用神经网络的逼近性质设计出了近似最优控制.利用Lyapunov稳定性定理,分析了多智能体误差系统的稳定性,并找到一个该误差系统最终有界的充分条件.数值仿真结果进一步验证了理论分析的有效性.     

Leader-following exponential consensus of general linear multi-agent systems via event-triggered control with combinational measurements

In this paper, the leader-following exponential consensus problem of general linear multi-agent systems via event-triggered control is considered. By using the combinational measurements, two classes of event triggers are designed, one depends on continuous communications between the agents, the other avoids continuous communications. For such two classes of event triggers, the exponential consensus as well as the convergence rates of the controlled multi-agent systems are studied, respectively, by employing the M-matrix theory, algebraic graph theory and the Lyapunov method.     

A class of distributed optimization methods with event-triggered communication

We present a class of methods for distributed optimization with event-triggered communication. To this end, we extend Nesterov’s first order scheme to use event-triggered communication in a networked environment. We then apply this approach to generalize the proximal center algorithm (PCA) for separable convex programs by Necoara and Suykens. Our method uses dual decomposition and applies the developed event-triggered version of Nesterov’s scheme to update the dual multipliers. The approach is shown to be well suited for solving the active optimal power flow (DC-OPF) problem in parallel with event-triggered and local communication. Numerical results for the IEEE 57 bus and IEEE 118 bus test cases confirm that approximate solutions can be obtained with significantly less communication while satisfying the same accuracy estimates as solutions computed without event-triggered communication.     

A note on the consensus finding problem in communication networks with switching topologies

In this note, we discuss the problem of consensus finding in communication networks of agents with dynamically switching topologies. In particular, we consider the case of directed networks with unbalanced matrices of communication rates. We formulate sufficient conditions for consensus finding in terms of strong connectivity of the underlying directed graphs and prove that, given these conditions, consensus is found asymptotically. Moreover, we show that this consensus is an emergent property of the system, being encoded in its dynamics and not just an invariant of its initial configuration.     

Event-triggered dual-mode predictive control for constrained nonlinear systems with continuous/intermittent detection

This paper investigates the problem of event-triggered model predictive control for constrained nonlinear systems. A dual-mode control strategy combined with two different event-triggered mechanisms are introduced to reduce computational and communication loads. For the event-triggered mechanisms, two cases, continuous detection and intermittent detection, are considered, respectively. In order to avoid the transmission of continuous predicted control input trajectories, the actual control signals are generated under a sample-and-hold manner. A decreasing prediction horizon is introduced to reduce the complexity of optimization problems and a tightened state constraint is designed to achieve robust constraint satisfaction. The sufficient conditions are derived to guarantee the feasibility and stability of the closed-loop system. The performance of the proposed strategy is illustrated by a simulation example.     

Stabilization of switched linear systems using an improved event-triggered control scheme

This paper is concerned with the event-triggered control of switched linear systems. The coupling of system switching and event-triggered communication raises two phenomena: (1) the update of controller cannot always catch up with the active subsystem; (2) the switching may lead to additional triggers. The first phenomenon is called the asynchronous switching induced by network communication and the second one brings great difficulty to avoid the Zeno behavior of event-triggered mechanism (ETM). To address the above problem, we propose a new ETM which contains the switching signal of models and controllers and the discontinuity of triggering error at switching time instants. A relative threshold strategy, combined with a jump function, is designed as a new threshold function. By introducing a compensation term, the linear feedback control law is extended to avoid the Zeno behavior of ETM and improve the solvability of control algorithm. Based on the proposed event-triggered control scheme, the exponential stabilization of switched systems is achieved with relaxed constraints on the triggering and switching conditions. The obtained results are validated by a numerical example.     

Quantized control for networked switched systems under denial-of-service attacks via a barrier event-triggered mechanism

This paper studies the quantized control problem for networked switched systems (NSSs) under denial-of-service (DoS) attacks. The quantized state information, together with the switching signal, is transmitted to the controller through a network. In order to reduce communication consumption and controller update frequency, a barrier event-triggered mechanism is utilized to monitor the state at discrete time. Because of the event-triggered mechanism and the DoS attacks on the network, the mismatch between the system mode and the controller mode is thus frequently encountered, which may lead to quantization saturation and system instability. To solve the problem, an update rule is presented for the dynamic quantizer by switching between zooming in and zooming out of the zooming variable, and a feedback controller is proposed with a jointly designed event-triggered mechanism and a dynamic quantizer. Sufficient conditions on the constraints of DoS frequency and duration are obtained to ensure the exponential stability of the switched system. The effectiveness of the obtained results is illustrated by simulation examples and comparative studies.     

Event-triggered impulsive control of lower-triangular large-scale nonlinear systems based on gain scaling technique

This paper investigates the event-triggered impulsive control problem for a class of large-scale nonlinear systems in lower-triangular form. Based on gain scaling technique and impulsive control theory, a novel decentralized event-triggered impulsive control strategy is first put forward by introducing a static scaling gain, where no control input exists between two consecutive triggering points. Moreover, when the large uncertainties exist in system nonlinearities, we further develop a new control strategy by introducing a time-varying scaling gain. It is proved that the proposed closed-loop control strategies exclude the Zeno behavior without sacrificing the global convergence of system states. Compared with the existing results, it is the first time to apply impulsive control to lower-triangular large-scale nonlinear systems, and the advantages of event-triggered impulsive control and gain scaling technique are subtly combined in the proposed control strategies. Finally, two simulation examples are used to demonstrate the effectiveness of the proposed schemes.     

非平衡拓扑和随机干扰情形下多自主体系统的趋同条件

研究了具有一般有向通信拓扑和高斯通信噪声的多自主体系统的趋同条件.这里所研究的有向拓扑不仅包含有向平衡图,而且包含非平衡图,后者是本文的重点.我们利用马氏链的结果得到了一个网络节点的互通类;通过对噪声影响的细化,给出了不同噪声情形下系统趋同条件:(1)对互通类的自主体获取信息受到噪声干扰情形,给出了系统均方趋同的充要条件,并证明该条件也保证以概率1 趋同;(2)对互通类的自主体获取信息未受到噪声干扰但其余自主体获取信息受到干扰情形,给出了系统均方趋同的充分条件,并证明该条件在一定意义下也是必要的;(3)对整个系统无噪声情形,给出了系统趋同的充要条件.     

Randomization helps to perform independent tasks reliably

This paper is about algorithms that schedule tasks to be performed in a distributed failure‐prone environment, when processors communicate by message‐passing, and when tasks are independent and of unit length. The processors work under synchrony and may fail by crashing. Failure patterns are imposed by adversaries. Linearly‐bounded adversaries may fail up to a constant fraction of the processors. Weakly‐adaptive adversaries have to select, prior to the start of an execution, a subset of processors to be failure‐prone, and then may fail only the selected processors, at arbitrary steps, in the course of the execution. Strongly adaptive adversaries have a total number of failures as the only restriction on failure patterns. The measures of complexity are work, measured as the available processor steps, and communication, measured as the number of point‐to‐point messages. A randomized algorithm is developed, that attains both ??(n log*n) expected work and ??(n log*n) expected communication, against weakly‐adaptive linearly‐bounded adversaries, in the case when the numbers of tasks and processors are both equal to n. This is in contrast with performance of algorithms against strongly‐adaptive linearly‐bounded adversaries, which has to be Ω(n log n/log log n) in terms of work. © 2003 Wiley Periodicals, Inc. Random Struct. Alg., 2004     

Sampled-data distributed protocol for coordinated aggregation of multi-agent systems subject to communication delays

This paper studies the coordinated aggregation problem of a multi-agent system. Particularly, all the agents reach a consensus within a pre-specified target region. However, only a subset of agents have access to this target region, and each agent merely interacts with its neighbors by communication. Moreover, there exist unknown heterogeneous delays in communication channels. The underlying communication topology is characterized by a digraph. To accommodate the practical digital disposal, a sampled-data distributed protocol is proposed, where the sampling is asynchronous in the sense that the sampling periods of distinct agents are heterogeneous. The resulting closed-loop system from the proposed sampled-data distributed protocol is in a hybrid fashion that the continuous system is fed-back by using discrete states at sampling instants. The convergence performance of this hybrid closed-loop system is analyzed based on the contraction theory. More specifically, it is first shown that all the states are coordinated to aggregate within the target region, i.e., coordinated aggregation. With this result, it is next shown that all the states are coordinated towards a consensus, i.e., state agreement. These together guarantee the fulfillment of the concerned coordinated aggregation objective. Finally, a simulation example is given to validate the theoretical results.     

Distributed event-triggered hybrid wired-wireless networked control with $${H_2}/{H_\infty }$$ filtering

Aiming at the fact that distributed multi-channel hybrid network-induced delays and noise interference may deteriorate the control performance of hybrid networked control systems, distributed event-triggered hybrid wired-wireless networked control with \({H_2}/{H_\infty }\) filtering is proposed. A distributed event-triggered mechanism is firstly employed to reduce communication burden, and two Markov chains are used to respectively describe different characters of network-induced delays of hybrid wired-wireless networks. Then, a \({H_2}/{H_\infty }\) filter is employed to improve the input signal precision of the controller, where a general closed-feedback filtering and control system model with distributed event-triggered parameters and network-induced delays of hybrid wired-wireless networks is proposed. Furthermore, the designed filter and controller enable the closed-feedback filtering and control system to be stochastic stability and to achieve a prescribed \({H_2}/{H_\infty }\) performance, and the relationships between the stability criteria and the maximum network-induced delays, distributed event-triggered parameters, the filter and controller parameters and the system performance parameter are established. Finally, simulation results confirm the effectiveness of the proposed method.     

Event-triggered and self-triggered impulsive control for two-time-scale systems

This paper studies the stability problem of two-time-scale system via event-triggered impulsive control and self-triggered impulsive control. The overall system is modeled with the hybrid formalism. Two Chang transformations are introduced to completely decouple the hybrid system states into flow set and jump set. A composite impulsive controller based on slow and fast system states is proposed, under which the slow and fast subsystems are simultaneously triggered by event-triggered and self-triggered mechanism, respectively. As a result, the stability conditions are derived for the system under event-triggered and self-triggered impulsive control, respectively. Furthermore, the theoretical result of self-triggered impulsive control is applied to the consensus of the interconnected two-time-scale systems. Finally, simulation examples and comparison study show the effectiveness of the proposed control strategies.     

Game-Theory-Based Consensus Learning of Double-Integrator Agents in the Presence of Worst-Case Adversaries

This work proposes a game-theory-based technique for guaranteeing consensus in unreliable networks by satisfying local objectives. This multi-agent problem is addressed under a distributed framework, in which every agent has to find the best controller against a worst-case adversary so that agreement is reached among the agents in the networked team. The construction of such controllers requires the solution of a system of coupled partial differential equations, which is typically not feasible. The algorithm proposed uses instead three approximators for each agent: one to approximate the value function, one to approximate the control law, and a third one to approximate a worst-case adversary. The tuning laws for every controller and adversary are driven by their neighboring controllers and adversaries, respectively, and neither the controller nor the adversary knows each other’s policies. A Lyapunov stability proof ensures that all the signals remain bounded and consensus is asymptotically reached. Simulation results are provided to demonstrate the efficacy of the proposed approach.     

基于马尔科夫拓扑切换和随机通信干扰的连续时间多自主体系统的趋同控制

研究了基于不可靠通信网络的连续时间多自主体系统的趋同控制.自主体间的通信信道受高斯噪声干扰;不可靠通信因素导致的网络拓扑随机切换由马氏链刻画.为克服随机噪声和马尔科夫拓扑切换的影响,设计了随机逼近型趋同协议;基于马氏跳参数随机微分方程稳定性理论、代数图理论、连续鞅和马氏链理论,证明了多自主体系统实现渐近无偏均方平均趋同...     

Event-triggered sliding mode control for switched genetic regulatory networks with persistent dwell time

This paper focus on the event-triggered sliding mode controller design for discrete-time switched genetic regulatory networks (GRNs) with persistent dwell time (PDT) switching. Firstly, the observation error dynamics of switched GRNs with PDT is constructed in the light of event-triggered sliding mode control (SMC) scheme. Next, sufficient conditions are derived to ensure the exponential stability of the augmented plant. Moreover, an event-triggered SMC law is synthesized to impel the system trajectories onto the sliding surface in a finite time. Finally, a verification example is provided to illustrate the effectiveness and potential of the proposed method.     

Small-gain technique-based adaptive output constrained control design of switched networked nonlinear systems via event-triggered communications

This paper investigates the problem of event-triggered tracking control for switched networked nonlinear systems with asymmetric time-varying output constraints. To handle the output constraints, an output-dependent generic constraint function is constructed to describe relationship between the output and the performance requirement. Meanwhile, an event-triggering rule is designed to reduce communication frequency between the controller and the actuator, thereby reducing the burden of the network communication. Based on the common Lyapunov function method and event-triggered control strategy, an adaptive control method is designed, which can guarantee that the closed-loop signals are bounded and avoid the Zeno behavior. Different from existing results considering constraints, the proposed scheme not only relaxes the restricted condition of constraint boundaries but also both the cases with and without output constraints can be addressed simultaneously. Furthermore, the stability of the system can be guaranteed by the small-gain technique. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed scheme.