短时滞的网络控制系统稳定性分析

针对具有时变传输时滞和间隔的网络控制系统(Networked Control Systems,NCSs)进行分析,基于传输时滞及输入时滞构建一种新的依赖于时间的非连续的Lyapunov泛函,提出新的稳定性准则.考虑零阶保持器更新时间在两个有效采样时间范围内,结合缩放方法及凸优化技术,最后通过线性矩阵不等式计算,得到新的...     

时变采样周期网络控制系统的鲁棒容错控制器设计

研究具有时变采样周期网络控制系统的执行器失效的完整性问题．假设系统任意两个连续采样间隔具有上界,利用输入时延法,将时变采样周期网络控制系统等价转化为连续时变时延网络控制系统．在此基础上,基于时延条件,应用Ｌｙａｐｕｎｏｖ稳定性理论和线性矩阵不等式（ＬＭＩｓ）方法证明了鲁棒容错控制律的存在条件,设计了鲁棒容错控制器,并给出了系统完整性条件下的最大允许时延的估计方法．仿真结果验证了所提方法的可行性和有效性．     

具有积分二次约束属性的网络控制系统H∞容错控制

针对一类具有积分二次约束属性的时滞网络控制系统,研究了系统在不等间隔采样下的H_∞容错控制.首先,分析并处理了网络控制系统中时滞与不等间隔采样之间的关系.以此为基础,建立了不等间隔采样下的不确定时滞网络控制系统的切换模型.通过构造Lyapunov函数,运用H_∞控制方法,以及设计具有积分二次约束属性的控制器,获得了基于LMI描述的系统时滞依赖稳定性判据.然后,建立了网络控制系统的传感器故障模型和传感器故障下的网络控制系统数学模型.通过把结论运用到传感器出现故障的网络控制系统,得到了系统在H_∞容错控制下的稳定性判据.最后,通过与其他文献介绍的方法进行比较的一个例子,说明了该方法的有效性.     

基于事件触发的神经网络控制器稳定性分析

针对非线性系统稳定性问题,设计了基于事件触发的神经网络控制器来稳定非线性系统,控制器只有在触发规则满足的条件下,才更新控制参数,降低了网络传输率。算法开始先建立非线性系统模型,在采样过程中引入事件触发机制,并且设计了神经网络控制器,对于系统中包含的传输时滞,引入系统时滞模型,运用输入延迟法将同步控制器求解问题转化为时滞系统的稳定性问题。再通过构造分段Lyapunov-Krasovskii泛函并结合Jensen不等式,给出了非线性系统稳定条件。与传统数据采样系统相比,本文所提出的方法有效地增大了采样间隔,结尾通过例子仿真验证了所提出方法的有效性。     

时变采样周期网络控制系统的鲁棒容错控制器设计

研究具有时变采样周期网络控制系统的执行器失效的完整性问题．假设系统任意两个连续采样间隔具有上界,利用输入时延法,将时变采样周期网络控制系统等价转化为连续时变时延网络控制系统．在此基础上,基于时延条件,应用Ｌｙａｐｕｎｏｖ稳定性理论和线性矩阵不等式（ＬＭＩｓ）方法证明了鲁棒容错控制律的存在条件,设计了鲁棒容错控制器,并给出了系统完整性条件下的最大允许时延的估计方法．仿真结果验证了所提方法的可行性和有效性．

     

双时滞离散模型的网络控制系统稳定条件

研究了具有双时滞离散线性系统的稳定性及其在网络控制中的应用。一个具有状态时滞的离散线性系统,假设它的状态信号从输出到控制器的时候,存在两种情况：第一种情况,有两条传播渠道,一条直接输入到控制器,另一条通过网络,网络传播往往会产生时滞;第二种情况是通过网络单渠道传送。基于Lyapunov稳定理论得到双时滞离散线性系统稳定的充分条件。在此基础上通过引入一些新的变量,将得到的条件转化为线性矩阵不等式（LMIs）,分别给出了两种情况下控制器的设计。最后给出的三个数值例子说明方法的有效性。     

网络控制系统的H∞状态反馈控制器设计

研究了对网络控制系统如何设计H∞状态反馈控制器.这些网络控制系统中存在不确定的网络时延和数据包丢失.当网络时延和连续丢包有界时,可以将系统建模为具有时变输入时滞的系统,利用Lyapunov-Krasovskii泛函,推导出网络控制系统渐近稳定的充分条件.将这些充分条件转化为带等式约束的LMIs,并对他们进行迭代求解,就可以构造H∞控制器.与现有结果相比,在推导稳定性条件时本文对交叉项采取了更紧的界定,并且在设计控制器时无需知道调节参数.因此,本文提出的方法具有更低的保守性.仿真结果说明了本方法的正确性和有效性.     

基于T-S 模糊模型的不确定时滞系统鲁棒??1 滤波

针对外部干扰信号为峰值有界的不确定时滞系统,提出一种新的基于T-S模糊模型的鲁棒1滤波方法.根据平行分布补偿法（PDC）和Lyapunov稳定性理论,构造模糊基依赖Lyapunov-Krasovskii泛函,并利用积分不等式方法,建立基于T-S模糊模型的不确定时滞系统的时滞相关峰值—–峰值（L₁）性能判据.最后通过LMI技术将鲁棒1滤波器设计问题转化为LMIs的凸优化求解问题.仿真示例验证了所提出方法的有效性.     

变时滞不确定组合系统基于观测器的鲁棒镇定

研究一类孤立子系统中状态及控制输入均含有时变时滞,且互联项也含有时变时滞的不确定组合系统基于状态观测器的鲁棒控制问题.基于一组线性矩阵不等式（LMIs）解的存在性,并依据Razumikhin-type理论和Lyapunov稳定性理论,给出了保证系统可鲁棒分散镇定的充分条件及相应控制器的设计方法.分散控制器可通过求解一组LMIs得到.最后,利用一个数值例子验证了所给设计方法的有效性.     

广义系统的时滞依赖静态输出反馈控制

针对一类不确定线性广义时滞系统,给出了静态输出反馈控制器的设计方法.首先基于标称广义时滞系统的稳定条件,以受限线性矩阵不等式形式,给出闭环广义时滞系统正则、无脉冲且渐近稳定的充分条件,同时利用受限矩阵不等式的可行解给出静态输出反馈控制律的一个参数化表示;其次,利用矩阵的正交补,把求受限线性矩阵不等式的可行解问题转化为求严格线性矩阵不等式(LMIs)的可行解;最后应用数值实例说明了所给方法的有效性和正确性.     

Random stabilization of sampled-data control systems with nonuniform sampling

For a sampled-data control system with nonuniform sampling, the sampling interval sequence, which is continuously distributed in a given interval, is described as a multiple independent and identically distributed (i.i.d.) process. With this process, the closed-loop system is transformed into an asynchronous dynamical impulsive model with input delays. Sufficient conditions for the closed-loop mean-square exponential stability are presented in terms of linear matrix inequalities (LMIs), in which the relation between the nonuniform sampling and the mean-square exponential stability of the closed-loop system is explicitly established. Based on the stability conditions, the controller design method is given, which is further formulated as a convex optimization problem with LMI constraints. Numerical examples and experiment results are given to show the effectiveness and the advantages of the theoretical results.     

A recursive algorithm for estimating multiple models continuous transfer function with non-uniform sampling

A multiple model recursive least squares algorithm combined with a first-order low-pass filter transformation method, named λ-transform, is proposed for the simultaneous identification of multiple model orders continuous transfer functions from non-uniformly sampled input–output data. The λ-transformation is shown to be equivalent to a canonical transformation between discrete z-domain and δ-domain using the negative value of the λ-transform filter time-constant instead of the sampling interval parameter. The proposed algorithm deals with oversampling, sampling jitter or non-uniform sample intervals without the need for extra digital anti-aliasing pre-filtering, downsampling or interpolation algorithms, producing multiple models with a cost function that facilitates automatic selection of best-fitted models. Besides, measurement noise is noted as beneficial, bringing up an inherent bias toward low-order models. Simulated examples and a drum-boiler level experimental result exhibiting non-minimum phase behaviour illustrate the application of the proposed method.     

观测器为基础的多包传输网络化系统故障检测

研究了基于不确定马尔科夫模型的多包传输网络化系统故障检测问题.通过引入传输矩阵形式,部分转移概率矩阵元素未知的马尔科夫跳系统模型被用来描述相邻采样周期不同数据包传输时的相关特性.基于获得的模型,利用李雅普若夫方法和随机分析技巧,建立了线性矩阵不等式形式充分条件,所得扩展的误差系统满足随机稳定性和H∞扰动水平.特别的,本文的结论可以包含经典马尔科夫模型和切换模型作为其特例.最后通过仿真例子说明了所用方法的有效性.     

OBSERVER-BASED HYBRID CONTROL OF SAMPLED-DATA UNCERTAIN SYSTEM WITH INPUT TIME DELAY

This paper proposes a new digital redesign method for determining the hybrid controller of a continuous-time system with input time delay using an observer-based digital controller. The proposed method together with the genetic algorithms is used to determine: (1) the interval digital model of a continuous-time uncertain system with input time delay, (2) the interval digital redesign control law and (3) the interval digital observer of the original continuous-time uncertain observer with input time delay. Moreover, the result is less conservative than those obtained by the existing interval methods. A discrete-time observer is built by the original continuous-time observer with input-time-delay control law and a predictor such that the estimated states of the redesigned discrete-time observer closely match those of the original continuous-time observer with input time delay not only at sampling instants but also the behavior of the system state during the sampling interval is optimal by minimizing the hybrid performance index. The digitally redesigned observer-based controller can closely match the states of the digitally redesigned uncertain sampled-data system with those of the original continuous-time observer-based controlled uncertain system with input time delay.     

Improved results for linear discrete-time systems with an interval time-varying input delay

This paper addresses the problem of delay-dependent stability analysis and controller synthesis for a discrete-time system with an interval time-varying input delay. By dividing delay interval into multiple parts and constructing a novel piecewise Lyapunov–Krasovskii functional, an improved delay-partitioning-dependent stability criterion and a stabilisation criterion are obtained in terms of matrix inequalities. Compared with some existing results, since a tighter bounding inequality is employed to deal with the integral items, our results depend on less number of linear matrix inequality scalar decision variables while obtaining same or better allowable upper delay bound. Numerical examples show the effectiveness of the proposed method.     

存在通信约束和时延的多输入多输出网络控制系统镇定研究

讨论了一类存在通信约束和时延的多输入多输出网络控制系统（NCS）的建模和控制问题.该NCS具有多个传感器和执行器，由于网络通信受限,在同一时刻只能允许部分传感器和执行器访问网络.传感器和执行器访问网络的过程可以用两个马尔可夫链来描述,并且在假设传感器—控制器时延和控制器—执行器时延均为短时延的情况下,将整个闭环NCS建模成一个具有两个模式的马尔可夫切换系统.基于LMI技术和李亚普诺夫方法,给出了闭环NCS随机稳定的充分条件,并给出了状态反馈控制器的设计方法.最后的数值算例验证了所提方法的有效性.     

Synchronization of Switched Neural Networks with Time‐varying Delays via Sampled‐data Control

This paper investigates sampled‐data synchronization control of switched neural networks with time‐varying delays under average dwell time. Based on the delay system method, the sampled‐data synchronization system is proposed with time‐varying delays and input delays in the unified framework for switched neural networks. By constructing a suitable Lyapunov‐Krasovskii functional and free‐weighting matrix, the relationship between the average dwell time and the maximum sampling interval is revealed to form delay‐dependent exponentially synchronization criteria. The desired mode‐dependent controller under the maximum sampling interval and decay rate is designed. Finally, two numerical examples are provided to demonstrate the effectiveness and feasibility of the proposed techniques.     

基于UIOs的风力机传动系统多故障诊断

风力机故障诊断通过对机组运行数据进行提取、估计,以辨别出故障并获得故障信息.但目前风力机故障检测大多考虑单个故障发生的情况,而实际工程中无法避免多故障同时发生.通过设计未知输入观测器组,解决了风力机传动系统执行器和传感器的多故障诊断及隔离.针对不同故障类型各设计一组未知输入观测器.观测器组中的每个未知输入观测器产生一个残差信号,该残差不敏感于相应故障,但敏感于其他故障.通过对比观测器组中的残差信号可实现单一或多故障诊断.建立风力机传动系统故障模型,仿真分析得出该方法具有可行性.     

Transmission scheduling algorithm for MIMO link ad hoc networks

Most reported works on transmission scheduling algorithm for multiple input multiple output (MIMO) link ad hoc networks do not fully exploit the spatial multiplexing potential inherent to multiple an-tennas system.In this paper,a novel transmission scheduling algorithm is proposed to further enhance the performance of MIMO link ad hoc networks.By utilizing the MIMO multi-stream reception capabilities and ordering the nodes’ allocation sequence,the proposed algorithm can dramatically shorten the scheduling frame length and more evenly distribute the data streams allocated to the network nodes.Meanwhile,allowing the nodes to transmit multiple streams in a slot,the algorithm can fully exploit the MIMO spatial multiplexing potential.Additionally,we give the theoretical analysis to quantify the throughput and delay performance with respect to this scheme.Numerical results demonstrate that the proposed algorithm can efficiently enhance the network throughput and reduce the average and maximum delay.