Distributed fuzzy adaptive event-triggered finite-time consensus tracking control for uncertain nonlinear multi-agent systems with asymmetric output constraint

This article investigates the consensus problem for uncertain nonlinear multi-agent systems (MASs) with asymmetric output constraint. Different from BLF-based constraint consensus tracking control, a novel approach based on nonlinear state-dependent function is proposed to solve the asymmetric output constraint, which need not convert output constraint into tracking error bound. First-order sliding mode differentiator is incorporated into each step of backstepping control design to reduce computation burden. Further, in combination of proposed event-triggered mechanism based on time-varying threshold, a distributed fuzzy adaptive event-triggered finite-time consensus method is developed. It can ensure that the consensus tracking error tends to a small neighbor in a finite time and the asymmetric output constraint of each subsystem is not violated. Two simulations are given to demonstrate the effectiveness of control method.     

A Novel Obstacle Avoidance Consensus Control for Multi-AUV Formation System

In this paper, the fixed-time event-triggered obstacle avoidance consensus control for a multi-AUV time-varying formation system in a 3D environment is presented by using an improved artificial potential field and leader-follower strategy(IAPF-LF). Firstly, the proposed fixed-time control can achieve the desired multi-AUV formation within a fixed settling time in any initial system state. Secondly, an event-triggered communication strategy is developed to govern the communication among AUVs, and...     

脉冲式事件触发控制的时变多个体系统一致性

针对时变拓扑连接环境下的时变多个体系统的一致性问题,提出基于事件触发的脉冲控制协议。在该协议里对于每个个体,只有当相关状态误差超过阈值时才会更新控制器,同时控制输入将仅在事件触发时刻执行,且个体间不需要持续通信。该协议将大幅节约系统实现一致性的通信和控制成本。使用代数图论、李雅普诺夫稳定性和脉冲微分方程等数学理论分析和推导具有时变特性的多个体系统在事件触发脉冲控制下达到一致性的充分条件,同时理论证明事件触发的时间序列不存在芝诺行为。最后,数值仿真验证了所得到的理论结论的有效性。     

Finite-time event-triggered control for a class of cascade switched affine nonlinear systems

This paper is concerned with the finite-time boundedness (FTB) problem of a class of cascade switched affine nonlinear systems. In order to avoid unnecessary waste of network communication and Zeno behavior, a dynamical event-triggered scheme is proposed, which is more general than some existing event-triggered schemes with a common parameter matrix. By using the average dwell time method and multiple Lyapunov function technologies, sufficient conditions for the existence of controller gains are first proposed such that the closed-loop system is finite-time bounded with a finite-time disturbance attenuation performance. It is also proved that the Zeno phenomenon is excluded. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.     

Event-triggered state estimation for T-S fuzzy affine systems based on piecewise Lyapunov-Krasovskii functionals

This paper investigates the problem of event-triggered ${\rm H}_\infty$ state estimation for Takagi-Sugeno (T-S) fuzzy affine systems. The objective is to design an event-triggered scheme and an observer such that the resulting estimation error system is asymptotically stable with a prescribed ${\rm H}_{\infty}$ performance and at the same time unnecessary output measurement transmission can be reduced. First, an event-triggered scheme is proposed to determine whether the sampled measurements should be transmitted or not. The output measurements, which trigger the condition, are supposed to suffer a network-induced time-varying and bounded delay before arriving at the observer. Then, by adopting the input delay method, the estimation error system can be reformulated as a piecewise delay system. Based on the piecewise Lyapunov-Krasovskii functional and the Finsler''s lemma, the event-triggered ${\rm H}_{\infty}$ observer design method is developed. Moreover, an algorithm is proposed to co-design the observer gains and the event-triggering parameters to guarantee that the estimation error system is asymptotically stable with a given disturbance attenuation level and the signal transmission rate is reduced as much as possible. Simulation studies are given to show the effectiveness of the proposed method.     

Event-triggered adaptive fuzzy control for nonstrict-feedback nonlinear systems with output hysteresis

This paper concentrates upon the issue of adaptive fuzzy tracing control for a class of nonstrict-feedback nonlinear systems output with hysteresis via an event-triggered strategy. To handle the difficulty caused by the nonstrict nonlinear systems, the variable separation technique is introduced. The design difficulty of output hysteresis is addressed by employing a hysteresis inverse function and Nussbaum function to compensate unmeasurable state signal. Meanwhile, the fuzzy logic system (FLS) is used to estimate the unknown function at each step of recursion. Moreover, by devising the relative threshold event-triggered mechanism (ETM), the frequency of actuators and controllers can be largely decreased. Thus, the adaptive fuzzy event-triggered tracing control strategy is proposed by combining the barrier Lyapunov function and backstepping technique. With the proposed scheme, it is theoretically demonstrated that all signals in the closed-loop system are bounded, and the tracing errors are driven to a small neighborhood of the origin under the output constraint. Eventually, two examples demonstrate the efficacy of the proposed control strategy.     

Event-triggered adaptive consensus control of nonlinear multi-agent systems with unknown control directions and actuator saturation

This article addresses the event-triggered adaptive consensus control of nonlinear multi-agent systems with unknown control direction and actuator saturation. A new robust adaptive control algorithm based on an event-triggered mechanism is designed. The smooth Lipschitz function approximates the saturated nonlinear function, while the Nussbaum function handles unknown control directions and residual terms. The event-triggered mechanism is designed to determine the time of communication, significantly reducing the communication burden. An additional estimator is utilized to deal with unknown parameters involved in neighbor dynamics and prevent information exchange to consistency errors between connected subsystems. The results show that all the signals of the closed-loop system are uniformly bounded, and the consensus tracking error converges to a bounded set. Meanwhile, Zeno's behavior is eliminated. Simulation results confirm the superiority of the proposed method.     

具有指定性能和全状态约束的多智能体系统事件触发控制

针对一类非严格反馈的非线性多智能体系统一致性跟踪问题,在考虑全状态约束和指定性能的基础上提出了一种事件触发自适应控制算法.首先,通过设计性能函数,使跟踪误差在规定时间内收敛于指定范围.然后,在反步法中引入Barrier Lyapunov函数使所有状态满足约束条件,结合动态面技术解决传统反步法产生的"计算爆炸"问题,并利用径向基函数神经网络（Radial basis function neural networks,RBF NNs）处理系统中的未知非线性函数.最后基于Lyapunov稳定性理论证明系统中所有信号都是半全局一致最终有界的,跟踪误差收敛于原点的有界邻域内且满足指定性能.仿真结果验证了该控制算法的有效性.     

通信延时和数据丢包下事件驱动的多智能体系统一致性研究

本文研究受网络通信延时和数据随机丢包的多智能系统一致性问题, 探索事件驱动的分布式协同控制策略. 首先针对两类普遍应用的事件触发器, 提出了一个可用于选择触发策略的触发频率比较方法. 然后提出了分布式协同控制律以保证系统的渐近一致性, 并给出了相应的时滞依赖Markov切换控制器设计新方法. 本文所提的控制策略不仅保证系统一致性目标, 而且能显著减少通信数据传输量并降低控制器计算负担. 最后,通过仿真算例验证了所提方法的有效性。     

基于事件触发的离散 MIMO 系统自适应评判容错控制

本文针对具有执行器故障的一类离散非线性多输入多输出(Multi-input multi-output, MIMO)系统, 提出了一种基于事件触发的自适应评判容错控制方案. 该控制方案包括评价和执行网络. 在评价网络里, 为了缓解现有的非光滑二值效用函数可能引起的执行网络跳变问题, 利用高斯函数构建了一个光滑的效用函数, 并采用评价网络近似最优性能指标函数. 在执行网络里, 通过变量替换将系统状态的将来信息转化成关于系统当前状态的函数, 并结合事件触发机制设计了最优跟踪控制器. 该控制器引入了动态补偿项, 不仅能够抑制执行器故障对系统性能的影响, 而且能够改善系统的控制性能. 稳定性分析表明所有信号最终一致有界且跟踪误差收敛于原点的有界小邻域内. 数值系统和实际系统的仿真结果验证了该方案的有效性.     

不对称欠驱动水面机器人事件触发全局渐近镇定控制

本文研究了不对称欠驱动水面机器人事件触发全局渐近镇定控制问题.首先,引入坐标变换将系统全局渐近镇定控制问题转化为变换后模型欠驱动子系统的全局渐近镇定控制问题,利用周期时间函数构造时变辅助变量提出了一种时变连续的镇定控制律,并结合切换门限事件触发机制设计实际的事件触发推力与力矩控制输入使闭环系统全局渐近稳定.所提出的方法...     

Fixed time event-triggered control for high-order nonlinear uncertain systems with time-varying full state constraints

The fixed time event-triggered control for high-order nonlinear uncertain systems with time-varying full state constraints is investigated in this paper. First, the event-triggered control (ETC) mechanism is introduced to reduce the data transmission in the communication channel. In consideration of the physical constraints and engineering requirements, time-varying barrier Lyapunov function (BLF) is deployed to make all the system states confined in the given time-varying constraints. Then, the radial basis function neural networks (RBF NNs) are used to approximate the unknown nonlinear terms. Further, the fixed time stability strategy is deployed to make the system achieve semiglobal practical fixed time stability (SPFTS) and the convergence time is independent of the initial conditions. Finally, the proposed control scheme is verified by two simulation examples.     

一种基于切换拓扑和事件触发机制的一致性协议

研究了一种新的基于切换拓扑的事件触发一致性协议,该协议设计了两个事件触发器,包括智能体状态演化引发的收敛事件触发器和拓扑变化引发的拓扑事件触发器,并给出了与事件触发器有关的公共Lyapunov函数的稳定性分析和理论证明,还设计了一种基于约束集的网络连通算法,用于提高网络的连通性。仿真实验结果表明,新的协议能够使得系统收敛一致,有效降低智能体控制器的更新频率,减少系统能耗,提升网络的连通效果,能为事件触发控制的后续研究提供理论支撑。     

离散非线性零和博弈的事件驱动最优控制方案

在求解离散非线性零和博弈问题时,为了在有效降低网络通讯和控制器执行次数的同时保证良好的控制效果,本文提出了一种基于事件驱动机制的最优控制方案.首先,设计了一个采用新型事件驱动阈值的事件驱动条件,并根据贝尔曼最优性原理获得了最优控制对的表达式.为了求解该表达式中的最优值函数,提出了一种单网络值迭代算法.利用一个神经网络构建评价网.设计了新的评价网权值更新规则.通过在评价网、控制策略及扰动策略之间不断迭代,最终获得零和博弈问题的最优值函数和最优控制对.然后,利用Lyapunov稳定性理论证明了闭环系统的稳定性.最后,将该事件驱动最优控制方案应用到了两个仿真例子中,验证了所提方法的有效性.     

状态时延和全状态约束下的多智能体系统自适应事件触发控制

研究有向通信图下非线性多智能体系统的一致控制问题.首先,通过引入性能函数,使输出误差满足预定性能;其次,采用障碍Lyapunov函数,保证所有状态满足约束条件,结合李雅普诺夫-克拉索夫斯基(Lyapunov-Krasovskii,LK)泛函和杨氏不等式消除状态时延的影响,利用径向基函数神经网络(radial basis...     

Dynamic event-based consensus of multi-agent systems with secure mode resilient to DoS attack

In this article, the resilient leaderless consensus problem for a multi-agent system (MAS) under denial-of-service(DoS) attack is investigated. The DoS attack is carried out with multiple strategies. The sufficient condition for MASs achieving consensus under multi-mode DoS attack is developed. In order to actively alleviate the influence caused by the DoS attack, the MAS switches between normal and secure modes. Once a DoS attack occurs, the agents will switch into the secure mode with a lower open-loop divergence rate. A dynamic event-based consensus protocol is proposed, driving the MAS achieve consensus while saving communication resources effectively. Moreover, rigorous proof analysis demonstrates the Zeno-free property of the developed dynamic event-triggered mechanism. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed theoretical results.     

Dynamic event-triggered bipartite consensus for uncertain high-order nonlinear multi-agent systems

In this paper, the bipartite consensus problem is studied for a class of uncertain high-order nonlinear multi-agent systems. A signed digraph is presented to describe the collaborative and competitive interactions among agents. For each agent with lower triangular structure, a time-varying gain compensator is first designed by relative output information of neighboring agents. Subsequently, a distributed controller with dynamic event-triggered mechanism is proposed to drive the bipartite consensus error to zero. It is worth noting that an internal dynamic variable is introduced in triggering function, which plays an essential role in excluding the Zeno behavior and reducing energy consumption. Furthermore, the dynamic event-triggered control protocol is developed for upper triangular multi-agent systems to realize the bipartite consensus without Zeno behavior. Finally, simulation examples are provided to illustrate the effectiveness of the presented results.     

Event-triggered adaptive control based on integral sliding mode surface for a class of linear systems with matched disturbance

In this paper, we propose an event-triggered adaptive integral sliding mode control scheme for a class of linear systems with external disturbance. In this method, the controller is designed using a triggered-state-dependent integral sliding mode, which can ensure the robustness and avoid the shortcomings of traditional sliding mode arrival stage. The triggering mechanism utilizes a time-varying trigger threshold instead of a traditional fixed threshold, which not only realizes the dynamic update of the control law, reduces the overhead of network communication but also ensures that the system trajectory enters the bounded area. The lower bound of inter event time guarantees the avoidance of the Zeno phenomenon. Next, in order to reduce the impact of high-frequency chattering of the control signal effectively and allow the gain of the discontinuous control term to be adjusted automatically according to the rate of change of the disturbance, a dual-layer nested adaptive gain scheme based on equivalent control is considered. This scheme does not require a priori boundedness of the disturbance and its rate of change. Through Lyapunov stability analysis, the event-triggered adaptive sliding mode controller can make the system trajectory converge in finite time and ensure the robustness of the control. Finally, the simulation results verify the effectiveness and simplicity of this method.     

Edge event-triggered control for multi-agent systems under directed communication topologies

The edge event-triggered consensus control for multi-agent systems with single- or double-integrator dynamics under directed communication topologies is investigated in this paper. With the edge event-triggered sampling strategies, a class of novel consensus protocols is proposed to reduce control update frequency. The main features of the proposed edge event-triggered control include three aspects: (i) measurement errors are defined based on directed information flow and thus they allow that the communication topology is directed, (ii) each individual controller updates its output only when the associated edge event occurs and the control actions are independent of other agents, and (iii) the proposed edge event-triggered control does not exhibit Zeno behaviour and it is shown that the inter-event intervals are lower bounded by a positive constant. In the consensus analysis, matrix transformation techniques are used to convert the high-dimensional system into a low-dimensional system, and some sufficient consensus conditions are derived for the multi-agent systems with single- or double-integrator dynamics. Finally, the effectiveness of the edge event-triggered sampling strategies is illustrated by simulations.     

基于事件触发的二阶多智能体系统平均一致性

针对二阶多智能体系统在固定无向拓扑下的平均一致性问题,为减少不必要的资源浪费,给出一种基于事件触发控制的一致性算法．首先,针对每个智能体设计基于状态误差形式的触发函数,只有当状态误差达到特定值时智能体才触发事件,在两个相邻事件触发时刻之间保持控制输入不变．然后,利用模型转换思想将系统的一致性问题转化为稳定性问题,并利用矩阵理论和李亚普诺夫理论给出系统达到平均一致的充分条件．最后,通过仿真实验验证该理论方案的有效性.