Stochastic bounded consensus tracking of leader-follower multi-agent systems with measurement noises and sampled-data

<正>This paper is concerned with the stochastic bounded consensus tracking problems of leader-follower multi-agent systems,where the control input of an agent can only use the information measured at the sampling instants from its neighbours or the virtual leader with a time-varying reference state,and the measurements are corrupted by random noises.The probability limit theory and the algebra graph theory are employed to derive the necessary and sufficient conditions guaranteeing the mean square bounded consensus tracking.It is shown that the maximum allowable upper boundary of the sampling period simultaneously depends on the constant feedback gains and the network topology. Furthermore,the effects of the sampling period on the tracking performance are analysed.It turns out that from the view point of the sampling period,there is a trade-off between the tracking speed and the static tracking error. Simulations are provided to demonstrate the effectiveness of the theoretical results.     

Stochastic bounded consensus tracking of leader-follower multi-agent systems with measurement noises based on sampled data with general sampling delay

In this paper we provide a unified framework for consensus tracking of leader-follower multi-agent systems with measurement noises based on sampled data with a general sampling delay. First, a stochastic bounded consensus tracking protocol based on sampled data with a general sampling delay is presented by employing the delay decomposition technique. Then, necessary and sufficient conditions are derived for guaranteeing leader-follower multi-agent systems with measurement noises and a time-varying reference state to achieve mean square bounded consensus tracking. The obtained results cover no sampling delay, a small sampling delay and a large sampling delay as three special cases. Last, simulations are provided to demonstrate the effectiveness of the theoretical results.     

基于有限区域量化的系统稳定性分析与设计

针对基于输出反馈和具有有限区域信号量化的离散时间系统,进行了系统稳定性分析与量化参数设计的研究.首先,分别对状态观测误差系统和对象系统在有限区域对数量化作用下的系统渐近稳定性进行了分析,得到了相应的稳定性条件,接着针对对数型量化器,给出了两个系统稳定性之间的内在关联,同时得到了各有限区域量化器的量化区间上界值.在此基础上,得到了保证各子系统稳定的系统通信速率比值.最后,给出了在时变量化作用下基于状态观测的控制策略和仿真例子.     

Asymptotic bounded consensus tracking of double-integrator multi-agent systems with bounded-jerk target based on sampled-data without velocity measurements

This paper investigates asymptotic bounded consensus tracking(ABCT) of double-integrator multi-agent systems(MASs) with an asymptotically-unbounded-acceleration and bounded-jerk target(AUABJT) available to partial agents based on sampled-data without velocity measurements. A sampled-data consensus tracking protocol(CTP) without velocity measurements is proposed to guarantee that double-integrator MASs track an AUABJT available to only partial agents.The eigenvalue analysis method together with the augmented matrix method is used to obtain the necessary and sufficient conditions for ABCT. A numerical example is provided to illustrate the effectiveness of theoretical results.     

Fault-tolerant finite-time dynamical consensus of double-integrator multi-agent systems with partial agents subject to synchronous self-sensing function failure

This paper investigates fault-tolerant finite-time dynamical consensus problems of double-integrator multi-agent systems (MASs) with partial agents subject to synchronous self-sensing function failure (SSFF). A strategy of recovering the connectivity of network topology among normal agents based on multi-hop communication and a fault-tolerant finite-time dynamical consensus protocol with time-varying gains are proposed to resist synchronous SSFF. It is proved that double-integrator MASs with partial agents subject to synchronous SSFF using the proposed strategy of network topology connectivity recovery and fault-tolerant finite-time dynamical consensus protocol with the proper time-varying gains can achieve finite-time dynamical consensus. Numerical simulations are given to illustrate the effectiveness of the theoretical results.     

时延网络控制系统的协同设计方法研究

在搭建的虚拟平台上对多任务的网络控制系统调度和嵌入LQG控制算法进行了仿真.探索了网络控制系统中调度与控制协同设计方法,讨论系统采样周期对网络控制系统的影响.以优化控制系统的性能为目标,以网络的可调度性为条件,结合系统控制和调度算法,对网络控制系统进行静态性能指标估计和动态调度仿真相结合.结果表明该方法既满足了控制系统的性能,又优化了网络的调度,提高了网络的资源率.     

输入受限的混沌系统同步控制

在混沌系统的同步控制中, 由于混沌系统对初始状态的敏感性, 一旦两个混沌系统的状态初值偏差大, 其状态同步往往需要高幅值的控制律来达到, 这给同步控制实现带来了困难, 并且在同步控制中, 两个混沌系统的初始值通常是未知的. 本文考虑控制输入受限情况下的混沌同步控制问题, 基于符号函数的近似表示式, 将受限的控制输入建模为连续可微的光滑函数, 在每一个采样点将同步控制误差系统近似为局部最优线性模型并设计连续型线性二次型调节器(LQR)最优控制律. 为降低混沌同步控制律的幅值和维持同步系统采样时刻之间的动态, 设计了等价的离散最优控制律, 并通过调整LQR性能加权矩阵值, 确保同步控制信号不会超出其受限的上界. 最后对统一混沌模型下的三种不同混沌系统同步控制进行了仿真研究. 仿真结果验证了方法的有效性. 关键词： 统一混沌模型 符号函数 输入受限 同步控制