Leader-following consensus of single-integrator multi-agent systems under noisy and delayed communication

This paper proposes a leader-following consensus control for continuous-time single-integrator multi-agent systems with multiplicative measurement noises and time-delays under directed fixed topologies. Each agent in the team receives imprecise information states corrupted by noises from its neighbours and from the leader; these noises are depending on the agents’ relative states information. Moreover, the information states received are also delayed by constant or time-varying delays. An analysis framework based on graph theory and stochastic tools is followed to derive conditions under which the tracking consensus of a constant reference is achieved in mean square. The effectiveness of the proposed algorithms is proved through some simulation examples.     

具有一步随机通讯时延的网络化切换系统H∞滤波

针对数据包在网络中传输的一步随机时延情形,研究任意切换律作用下的离散切换系统的H∞滤波问题.时延数据包包含系统的测量输出信号和切换信号,其时延由一个满足Bernoulli分布的随机变量来描述.选用切换Lyapunov函数,设计全阶和降阶的切换滤波器使得滤波误差系统在均方意义下指数稳定且具有扰动衰减度γ.滤波器的参数通过...     

New approach to stochastic stability and controller design for networked control systems

This paper addresses the random time-delays and packet losses issues of networked control systems (NCS) within the framework of jump linear systems with mode-dependent time-delays.A new delay-dependent condition on the stochastic stability is proposed by a new stochastic Lyapunov-Krasovskii functional.The condition is formulated as a set of coupled linear matrix inequalities (LMIs).As an example to verify the proposed method,an inverted-pendulum system with network is considered.The simulation results demonstrate the effectiveness of the method.     

New approach to stochastic stability and controller design for networked control systems

This paper addresses the random time-delays and packet losses issues of networked control systems （NCS） within the framework of jump linear systems with mode-dependent time-delays. A new delay-dependent condition on the stochastic stability is proposed by a new stochastic Lyapunov-Krasovskii functional. The condition is formulated as a set of coupled linear matrix inequalities （LMIs）. As an example to verify the proposed method, an inverted-pendulum system with network is considered. The simulation results demonstrate the effectiveness of the method.     

基于辅助变量的压缩采样匹配追踪闭环系统辨识方法

针对被控对象和反馈通道均具有未知时滞的闭环系统,提出一种基于辅助变量的压缩采样匹配追踪辨识方法.该方法利用辅助变量方法对压缩采样匹配追踪算法进行改进,获得过参数化辨识模型稀疏参数向量的估计,根据稀疏向量的结构得到前向通道的参数估计和时滞估计,进而根据模型等价原理获得反馈通道的参数估计.仿真结果表明,所提出方法仅需少量的迭代即可获得这类闭环系统参数与时滞的有效估计.     

A Linear Quadratic Control for Discrete Systems with Random Parameters and Multiplicative Noise and Its Application to Investment Portfolio Optimization

A quadratic control for discrete stochastic systems with random parameters and additive and multiplicative noises dependent on state and controls is studied. Equations for the optimal linear static and dynamic output controllers are derived. The controllers are robust to the type of the distribution of the vector of random parameters. The results are applied to dynamic investment portfolio optimization.     

一类随机时延网络化控制系统的容错控制研究

将一类具有随机时延的网络化控制系统建模为具有马尔可夫延迟特性的离散跳变线性系统．借助跳变线性系统理论和容错控制的思想，研究了随机时延网络化控制系统的执行器失效问题．仿真结果验证了所提方法的有效性．     

多组多滞后区间系数时变非线性关联控制系统的结构与关联鲁棒镇定（Ⅱ）

建立了多组多滞后区间系数时变非线性控制系统的结构概念，采用鲁棒镇定等价法，给出了具有扰动结构参数的多组多滞后区间系数时变非线性关联控制系统的结构与关联鲁棒镇定，同时给出了扰动参数与滞后非线性项界线的估计公式。     

Optimal Control of Nonlinear Stochastic Systems under Constraints: An Approximate Determination Method

An approximate method is developed for determining the optimal control for nonlinear stochastic systems under mixed equality- and inequality-type constraints on the parameters of the system, control functions, and phase coordinate in the presence of random parameters and additive and multiplicative noises. The method is based on the reduction of the initial stochastic problem to a deterministic problem for the cumulants of a random process described by stochastic differential equations.     

Recursive linear optimal filter for Markovian jump linear systems with multi-step correlated noises and multiplicative random parameters

This paper presents the state estimation problem for discrete-time Markovian jump linear systems with multi-step correlated additive noises and multiplicative random parameters (termed as MCNMP). A recursive linear optimal filter for the considered MCNMP (which is abbreviated as RLMMF) is derived based on state augmentation between the original state and mode uncertainty, with the help of estimating the multi-step correlated additive noises online simultaneously. A maneuvering target tracking example under one-step and two-step correlated additive noises scenarios with different cases (i.e. Gaussian/Gaussian mixture distribution and no multiplicative noises) is simulated to validate the designed filter.