Event-Triggered Finite-Time H∞ Filtering for Discrete-Time Nonlinear Stochastic Systems

This paper addresses the problem of event-triggered finite-time H∞ filter design for a class of discrete-time nonlinear stochastic systems with exogenous disturbances. The stochastic Lyapunov-Krasoviskii functional method is adopted to design a filter such that the filtering error system is stochastic finite-time stable (SFTS) and preserves a prescribed performance level according to the pre-defined event-triggered criteria. Based on stochastic differential equations theory, some sufficient conditions for the existence of H∞ filter are obtained for the suggested system by employing linear matrix inequality technique. Finally, the desired H∞ filter gain matrices can be expressed in an explicit form.

Time-varying formation for general linear multi-agent systems via distributed event-triggered control under switching topologies

This paper investigates the time-varying formation problem for general linear multi-agent systems using distributed event-triggered control strategy.Different from the previous works,to achieve the desired time-varying formation,a distributed control scheme is designed in an event-triggered way,in which for each agent the controller is triggered only at its own event times.The interaction topology among agents is assumed to be switching.The common Lyapunov function as well as Riccati inequality is applied to solve the time-varying formation problem.Moreover,the Zeno behavior of triggering time sequences can be excluded for each agent.Finally,a simulation example is presented to illustrate the effectiveness of the theoretical results.

Event-Triggered Finite-Time <i>H</i>_∞Control for Switched Stochastic Systems

This paper investigates the problem of event-triggered finite-time H∞ control for a class of switched stochastic systems. The main objective of this study is to design an event-triggered state feedback H∞ controller such that the resulting closed-loop system is finite-time bounded and satisfies a prescribed H∞ level in some given finite-time interval. Based on stochastic differential equations theory and average dwell time approach, sufficient conditions are derived to ensure the finite-time stochastic stability with the prescribed H∞ performance for the relevant closed-loop system by employing the linear matrix inequality technique. Finally, the desired state feedback H∞ controller gain matrices can be expressed in an explicit form.

Event-Triggered Zero-Gradient-Sum Distributed Algorithm for Convex Optimization with Time-Varying Communication Delays and Switching Directed Topologies

Nowadays, distributed optimization algorithms are widely used in various complex networks. In order to expand the theory of distributed optimization algorithms in the direction of directed graph, the distributed convex optimization problem with time-varying delays and switching topologies in the case of directed graph topology is studied. The event-triggered communication mechanism is adopted, that is, the communication between agents is determined by the trigger conditions, and the information exchange is carried out only when the conditions are met. Compared with continuous communication, this greatly saves network resources and reduces communication cost. Using Lyapunov-Krasovskii function method and inequality analysis, a new sufficient condition is proposed to ensure that the agent state finally reaches the optimal state. The upper bound of the maximum allowable delay is given. In addition, Zeno behavior will be proved not to exist during the operation of the algorithm. Finally, a simulation example is given to illustrate the correctness of the results in this paper.

Event-Triggered Sliding Mode Control for Trajectory Tracking of Nonlinear Systems

In this paper, an event-triggered sliding mode control approach for trajectory tracking problem of nonlinear input affine system with disturbance has been proposed. A second order robotic manipulator system has been modeled into a general nonlinear input affine system. Initially, the global asymptotic stability is ensured with conventional periodic sampling approach for reference trajectory tracking. Then the proposed approach of event-triggered sliding mode control is discussed which guarantees semi-global uniform ultimate boundedness. The proposed control approach guarantees non-accumulation of control updates ensuring lower bounds on inter-event triggering instants avoiding Zeno behavior in presence of the disturbance. The system shows better performance in terms of reduced control updates, ensures system stability which further guarantees optimization of resource usage and cost. The simulation results are provided for validation of proposed methodology for tracking problem by a robotic manipulator. The number of aperiodic control updates is found to be approximately 44% and 61% in the presence of constant and time-varying disturbances respectively.

Event-triggered adaptive finite time trajectory tracking control for an under actuated vessel considering unknown time-varying disturbances

This paper aims to solve the finite-time trajectory tracking problem of underactuated surface ships under the influence of dynamic uncertainty,unknown external time-varying interference and limited communication resources.An event-triggered robust adaptive finite-time trajectory tracking control method for underactuated ships is designed by combining the existing trajectory tracking control methods and engineering needs in actual navigation.It can obviously improve the tracking accuracy of the ship,and complete the tracking task safely and efficiently.This scheme transforms the composite uncertain vector synthesized by uncertain parameters and external disturbances into a linear parameterized form.Next,considering the limitation of communication resources,a relative threshold event triggering mechanism is introduced to further extend the triggering time interval on the basis of the fixed threshold triggering scheme.Then,an event-triggered robust adaptive finite-time trajectory tracking control scheme is designed for underactuated ships,and a rigorous stability proof is provided through Lyapunov stability theory.Simulation experiment is carried out in MATLAB and the results show that the finite-time trajectory tracking control scheme proposed in this paper can effectively solve the problems of dynamic uncertainty.unknown time-varying external interference and limitation of communication resources.This paper can provide theoretical support for the autonomous navigation of intelligent ships.

一种基于Event-B语言的时间触发系统建模方法

安全关键信息物理系统的时间属性建模和验证至关重要。Event-B模型验证避免了基于状态遍历模型检查方法的状态空间爆炸问题,验证时耗少,适用于高并发系统。然而,常规的Event-B方法缺乏时间语义表达结构,特别是缺乏对可提高系统可预测性的时间触发属性的支持。首先,介绍支持时间触发系统的抽象建模框架TTEB,从系统行为和实现2个抽象层次对时间属性进行建模和精化。然后,通过有序事件链组成的时间触发转移描述行为层时间触发属性;通过全局时钟到分布式本地时钟的精化和分解实现行为模型到实现模型的转化;运用时间触发转移建模分布式时钟周期同步。最后,基于从车跟车系统建模与验证说明方法的可用性和有效性。

基于事件触发的预设时间航天器轨迹跟踪控制

针对通信受限条件下的航天器轨迹跟踪问题,提出了一种基于事件触发的预设时间控制算法。为了满足不同任务场景下对航天器快速性的要求,本文设计了一种预设时间轨迹跟踪控制算法。结合反步控制理论及预设时间动态增益,最终实现轨迹跟踪系统的预设时间收敛。作为一种典型的网络化控制系统,航天器在执行任务过程中可能会受到自身通信能力的限制,造成通信阻塞、时延和丢包等问题。为此,本文提出了一种基于动态参数的事件触发算法,在保证系统控制精度的同时,一定程度上避免了控制中心与航天器本体间不必要的通信资源消耗。相比于传统的静态事件触发算法,文中基于动态参数的事件触发算法在减少通信频率方面更具优势。通过理论分析和仿真实验验证所提控制算法的有效性。

考虑时延的异质协作车队事件触发控制研究

针对目前研究较少考虑车辆混行造成的异质问题与时延问题,本文提出了一种具有时延的异质协作式自动驾驶车队事件触发控制方法 .首先,建立了考虑混行的异质车辆时延模型;其次,基于PID(proportional-integral-derivative)控制与模型预测控制(MPC),设计了不同模式下的事件触发控制器;然后,在城市和紧急情况下,对所提出的控制器进行了仿真分析;最后,基于Jetson Nano模型车进行了实车实验.仿真与实验结果表明,所提出的事件触发控制方法能够在不同情况下更好地权衡控制精度与计算速度间的矛盾.在带有通信时延的紧急情况下,仍能够保持较低的误差.

自适应事件触发机制下分布时滞Markov跳变网络化系统H_(∞)故障检测

传统事件触发机制中阈值的选择会对信号传输效率产生很大影响。针对此问题,研究了自适应事件触发机制下具有分布时滞的Markov网络化系统的故障检测问题。设计了一种模态相关的自适应事件触发机制,通过动态调整阈值,提高了网络资源利用率。考虑网络时延和数据丢包现象,同步设计触发器和故障检测滤波器。构造模态相关的Lyapunov泛数,根据积分不等式技术推导出使系统随机稳定且具有H_(∞)性能的充分条件。利用解耦方法和LMI技术求解出了故障检测滤波器参数。最后通过数值仿真验证了方案在节省网络资源上的优势。

不确定非线性离散系统指令滤波事件触发控制

本文提出了考虑输入饱和的一类不确定非线性离散系统的事件触发指令滤波控制方法.采用指令滤波控制技术解决了传统反步法存在的“因果矛盾”问题,引入补偿机制提高了系统的控制精度;利用事件触发机制能够避免自适应律和控制律的频繁更新,降低了计算负担,提高了资源利用率;运用模糊逻辑系统逼近系统中未知的非线性函数;结合李雅普诺夫稳定性理论,验证了提出的控制方案能够保证跟踪误差收敛到原点小的邻域内以及闭环系统的所有信号有界.仿真结果表明,本文提出的控制方法具有较强的鲁棒性及较好的跟踪性能.

基于非线性仿射的风电场电压实时计算和优化方法

该文提出一种基于非线性仿射的风电场电压实时计算和优化方法。首先,以网损和并网电压波动综合最小为目标,建立风电场多时段动态无功优化模型,利用半不变量法分析风电功率不确定性对机端电压的影响,采用改进内点法实现模型的高效求解;其次,提出一种非线性仿射方法,快速准确地获得计及风电功率波动后的系统电压状态,并通过计算风机无功调节量来实现系统电压实时优化;再次,设计考虑风电功率对机端电压和并网电压综合影响的事件触发算法,降低风电功率波动平缓时风机的无功控制频率;最后,在我国某实际风电场的仿真试验表明,非线性仿射法能够快速获得系统实时电压状态,电压实时优化方法能够有效地防止机端电压越限并减小并网电压波动。

考虑量化和通信受限的有限时间确定学习控制及其应用

本文针对一类含有量化输入和外部扰动的严格反馈非线性系统,提出了一种考虑量化和通信受限的有限时间确定学习控制方法.该方法包含离线学习训练和在线触发控制两个阶段.首先,在离线学习训练阶段采用神经网络对系统中的未知非线性函数进行逼近,引入指令滤波反步技术克服“计算爆炸”的问题,并在控制过程中实现系统未知动态的知识获取和存储.随后,利用所获取的经验知识,设计了基于确定学习机制的在线触发控制器.应用李雅普诺夫稳定性理论证明了闭环系统实际有限时间稳定,跟踪误差在有限时间内收敛到原点的邻域内,并能够排除采样中的芝诺现象.最后,通过飞行器仿真验证了所提方案的有效性.

孤岛微电网固定时间分布式鲁棒二次控制

针对孤岛微电网实际运行过程中出现的未知外部扰动,提出了一种固定时间分布式鲁棒二次控制算法,实现了电网频率一致性控制,有效抑制了不确定干扰,提高了系统的鲁棒性能。首先,通过设计基于饱和函数的新型控制算法,有效地解决了现有控制器高频切换引发的抖动问题。同时确保二次控制能够在固定时间内达到稳定状态,且收敛时间上界不依赖于任何初始状态。然后,在设计控制算法的基础上,采用改进的分布式事件触发机制,在满足收敛速度和达到电网频率一致性的基础上减轻了通信负担,减少了控制器更新的频率,显著降低了通信资源的消耗,并排除了Zeno行为。最后,利用Matlab/Simulink仿真平台验证了所提控制算法的有效性。

动态事件触发下的一阶非线性多智能体系统设定时间一致性

为了保证多智能体系统收敛速度快的同时节约通信资源,针对一阶非线性多智能体系统提出了动态事件触发设定时间一致性算法.相较于传统的有限时间和固定时间控制算法,设定时间控制算法引入时变函数,可以保证系统在任意预设时间内均可达到一致性.同时,设定时间控制算法的收敛时间上界不依赖于系统初始状态、拓扑结构和控制参数,可以根据用户需求任意提前设置.故设定时间控制算法解决了计算冗杂的问题,同时可以保证控制精度.为了进一步减少触发次数,在现有的静态事件触发控制算法的基础上引入新的动态变量,进而设计出动态事件触发算法.动态变量随时间改变,可以降低触发次数,从而减少控制器更新频率和执行机构的磨损程度.鉴于非线性系统广泛存在于实际应用场景中,基于非线性系统设计的控制算法更具有一般性.最后,通过数值仿真验证动态事件触发设定时间一致性算法的有效性.综上,本文所提出的动态事件触发设定时间一致性算法可以保证一阶非线性系统在任意设定时间内实现一致性,并且减少触发次数,更可能应用于实际工程.

动态事件触发下多智能体系统固定时间一致性

针对具有未知干扰和非线性动态的多智能体系统,研究了它基于事件触发的固定时间一致性问题。在传统的静态事件触发策略的基础上,通过引入一个可调节的动态变量,提出一种基于动态事件触发策略的固定时间一致性协议,给出各个智能体基于状态信息和动态变量的动态事件触发函数,只有当各智能体的测量误差满足给定的触发函数时,事件才会被触发。引入的动态变量是可调节的阈值参数,能够进一步减少事件的触发次数,更有效地利用系统有限的资源。利用图论、固定时间一致性理论和李雅普诺夫稳定性理论推导出系统达到固定时间一致性时,一致性协议和触发函数中的参数需要满足的条件,同时证明了系统不存在芝诺行为。最后,数值仿真结果验证了理论分析的正确性与有效性。

一类时滞多智能体系统的事件触发容错控制

针对时变通讯时滞下,具有执行器故障和参数不确定性的多智能体系统事件触发一致性控制问题,利用线性矩阵不等式(LMI)技术,设计了反馈控制增益矩阵;为降低通信资源的消耗,设计了基于模型的动态事件触发机制;通过李雅普诺夫稳定性理论证明了容错控制算法在间歇通信的情况下实现了多智能体系统一致性,且排除了芝诺行为。

基于固定时间一致性算法的孤岛微电网事件触发二次频率控制

微电网传统一致性算法抗扰能力差、调节时间无法得到保证,控制器周期采样造成大量数据冗余,因此提出一种基于固定时间一致性算法的事件触发机制,实现了输出频率的恢复和有功功率按比例分配。所提出的控制策略提高了系统的收敛速度,实现了固定时间内系统稳定,减小了对系统初始状态的依赖。同时,引入事件触发机制,通过减少采样信息的传输节约了通信资源。利用Lyapunov理论证明了所提控制策略的稳定性。Matlab/Simulink仿真结果验证了本研究所提控制策略的有效性。

基于事件触发的奇异semi-Markov跳变系统的有限时间控制

为减少不必要的网络资源传输,解决实际复杂系统的有限时间问题,提出一种基于事件触发方案的奇异semi-Markov跳变系统的有限时间控制器设计方法。在事件触发方案下,用系统的时滞表示网络诱导时延,闭环系统可以建模为一个时滞系统。首先,通过构造合适的Lyapunov-Krasovskii泛函,以严格矩阵不等式的形式给出充分条件,以使事件触发方案下的闭环系统正则、无脉冲、随机有限时间有界;然后,通过求解矩阵不等式,得到状态反馈控制器的参数;最后,给出一个数值示例,通过仿真证明所提方法的有效性。

时变输出约束机械臂系统渐近跟踪控制

针对非对称时变输出约束的机械臂系统,提出了一种基于事件触发的自适应渐近跟踪控制策略。首先,采用自适应命令滤波反步方法,解决了“计算爆炸”问题;同时,利用时变非对称李雅普诺夫函数,可以保证闭环系统的渐近稳定性且系统状态满足非对称时变约束条件;此外,自适应渐近跟踪控制可以保证在存在不匹配扰动的情况下,跟踪误差渐近收敛于零。该控制器设计采用了事件触发控制策略,在必要时产生控制输入,减少通信负担,提高了控制性能;最后,通过对非对称时变约束下的双连杆机械臂系统进行仿真,验证了该方法的有效性。