An Optimal Tracking Performance of MIMO NCS with Quantization and Bandwidth Constraints

This paper presents an optimal tracking performance of multiple‐input multiple‐output (MIMO) networked control systems (NCSs) with quantization and bandwidth constraints. In this study, we simultaneously consider the encoding‐decoding, quantization and bandwidth of communication channel. The optimal tracking performance of NCSs is obtained by spectral factorization technique and partial fraction. The obtained results demonstrate that the optimal tracking performance is influenced by the nonminimum phase zeros and unstable poles as well as their directions for a given plant. In addition, it is shown that characteristics of reference signal, encoding‐decoding, quantization, and bandwidth of communication channel are also closely related to tracking performance. Finally, the efficiency of proposed tracking performance is verified by typical examples.     

Regulation performance limitation of networked time-delay systems with incomplete information

In this paper, the regulation performance limitation of networked time-delay systems is studied. The communication network is mainly affected by parameters such as packet dropouts, encoding-decoding, interference signal, and channel noises. Non-minimum phase zeros, unstable poles, and time delay are all considered for a given plant. The corresponding regulation performance expression is derived using coprime factorization and spectral decomposition techniques in the frequency domain. The results indicate that the regulation performance of the system is related to the inherent characteristics of the given plant, including non-minimum phase zeros, unstable poles, and time delay. Additionally, network communication parameters such as white Gaussian noise, packet dropouts, encoding-decoding, and external interference signals all affect the regulation performance of networked time-delay systems. Finally, some simulation examples are provided to demonstrate the effectiveness of the theory.     

基于丢包和带宽限制网络化系统稳定性分析

基于数据包丢失和网络带宽限制研究了网络化系统稳定性问题.通信网络的特征通过数据包丢失、带宽和加性白噪声来体现.采用频域的方法得到了网络化系统稳定所需信噪比的最小(极限)值.该最小(极限)值说明了网络化系统稳定所需信噪比是由通信网络通道的丢包率、带宽、系统的不稳定极点的位置和非最小相位零点的位置决定.研究结果进一步揭示网络化系统稳定所需信噪比的最小(极限)值与系统本质特征(非最小相位零点的位置和不稳定极点的位置)和通信网络参数(数据包丢失和带宽)的关系.仿真结果说明该理论的正确性.     

Iterative Learning Control With Incomplete Information: A Survey

This paper conducts a survey on iterative learning control (ILC) with incomplete information and associated control system design, which is a frontier of the ILC field. The incomplete information, including passive and active types, can cause data loss or fragment due to various factors. Passive incomplete information refers to incomplete data and information caused by practical system limitations during data collection, storage, transmission, and processing, such as data dropouts, delays, disordering, and limited transmission bandwidth. Active incomplete information refers to incomplete data and information caused by man-made reduction of data quantity and quality on the premise that the given objective is satisfied, such as sampling and quantization. This survey emphasizes two aspects: the first one is how to guarantee good learning performance and tracking performance with passive incomplete data, and the second is how to balance the control performance index and data demand by active means. The promising research directions along this topic are also addressed, where data robustness is highly emphasized. This survey is expected to improve understanding of the restrictive relationship and trade-off between incomplete data and tracking performance, quantitatively, and promote further developments of ILC theory.      

多通道约束下的网络控制系统的最优跟踪性能

本文针对双通道约束下的线性时不变网络控制系统的随机信号跟踪性能极限问题进行了研究.网络通信包含通信噪声和通信带宽两种信道因素.被控系统考虑是非最小相位和不稳定系统,并且系统包含多个不同的非最小相位零点和多个不同的不稳定极点.对上行通道和下行通道都存在通信带宽约束及高斯白噪声影响的情形,从频域角度,通过采用双自由度控制器和尤拉参数化方法,获得了此类网络控制系统的最优可达的跟踪性能.研究结果表明网络控制系统的跟踪性能极限完全由被控对象的结构特征(非最小相位零点、不稳定极点以及被控对象的系统增益),参考输入信号和网络特性(高斯白噪声的统计特征、通信信道带宽)所决定.最后,仿真结果检证了所得结果的正确性.     

网络控制系统动态量化H∞控制

基于线性矩阵不等式技术,采用状态反馈控制,考虑同时带有网络诱导随机丢包 和量化的H∞控制问题。考虑信号经网络从传感器到控制器和从控制器到执行器的传输中存在 通信诱导随机丢包,并采用动态量化器量化信号。设计H∞控制器的同时,提出量化的控制策 略,使得闭环系统在量化器的量化范围条件下指数均方稳定且具有指定的H∞性能指标。通过 数值仿真例子表明设计方法的有效性。     

具有数据丢包的非线性奇异脉冲系统量化控制

考虑网络传输中存在的数据丢包和信号量化问题, 研究了基于数据丢包的非线性奇异脉冲系统设量化反馈控制器的设计方法. 首先给出一般非线性奇异脉冲系统的数学描述, 并在此基础上建立相应的具有丢包的闭环量化反馈控制系统的数学模型. 其次, 根据李雅普诺夫稳定性理论, 给出了奇异脉冲系统的渐近稳定的充分条件以及量化反馈控制器的设计方法. 应用本设计方法, 可以选择满足代数矩阵不等式条件的量化反馈增益, 实现系统渐近稳定. 最后通过对Chua混沌系统仿真, 表明利用本文设计的量化控制器能够保证闭环非线性奇异脉冲系统在具有数据丢包的情况下渐近稳定.     

丢包扰动环境下基于强化学习的最优输出调节

针对存在线性外部干扰和状态反馈过程中发生丢包的网络控制系统的跟踪控制问题,采用输出调节的思想,提出基于离轨策略强化学习的数据驱动最优输出调节控制方法,实现仅利用在线数据即可求解控制策略.首先,对系统状态在网络传输过程存在丢包的情况,利用史密斯预估器重构系统的状态;然后基于输出调节控制框架,提出一种基于离轨策略强化学习的数据驱动最优控制算法,在系统状态发生丢包时仅利用在线数据计算反馈增益,在求解反馈增益过程中找到与求解输出调节问题的联系;接着基于求解反馈增益过程中得到的与输出调节问题中求解调节器方程相关的参数,计算前馈增益的无模型解;最后,通过仿真结果验证所提出方法的有效性.     

Optimal tracking performance of MIMO control systems with communication constraints and a code scheme

This paper investigates the issue of the optimal tracking performance for multiple-input multiple-output linear time-invariant continuous-time systems with power constrained. An H₂ criterion of the error signal and the signal of the input channel are used as a measure for the tracking performance. A code scheme is introduced as a means of integrating controller and channel design to obtain the optimal tracking performance. It is shown that the optimal tracking performance index consists of two parts, one depends on the non-minimum phase zeros and zero direction of the given plant, as well as the reference input signal, while the other depends on the unstable poles and pole direction of the given plant, as well as on the bandwidth and additive white noise of a communication channel. It is also shown that when the communication does not exist, the optimal tracking performance reduces to the existing normal tracking performance of the control system. The results show how the optimal tracking performance is limited by the bandwidth and additive white noise of the communication channel. A typical example is given to illustrate the theoretical results.     

具有时变时滞和多包丢失的网络控制系统量化H∞控制

研究了具有时变时滞与多数据包丢失的网络控制系统(networked control systems,NCSs)的量化H∞控制问题.同时考虑传感器-控制器间的测量通道及控制器-执行器间的控制通道的多数据包丢失,并将其用满足Bernoulli分布的随机变量来表示.控制输入信号和测量输出信号分别在传感器和控制器两侧进行对数量化,量化误差描述为扇区有界不确定性.利用Lyapunov理论和线性矩阵不等式方法,得到了使得闭环NCSs满足一定H∞性能指标的均方意义下指数稳定充分条件,并给出了基于观测器的时滞相关控制器设计方法.最后,通过实例证明了该方法的有效性.     

基于模型的网络化控制系统量化反馈镇定

研究一类线性不确定网络化系统信息受限情况下的模型控制问题.在被控系统和模型系统通过带宽受限网络相连的情况下给出了有效的量化方法,使得量化值能够在量化器的容许范围之内,并给出了系统在一定条件下渐近稳定的充分条件.最后的仿真算例表明了所提出方法的可行性.     

基于量化控制信号的线性系统的跟踪性能极限

研究基于量化控制信号的线性系统的跟踪性能极限. 所研究的被控对象是稳定的线性时不变(LTI)系统, 参考跟踪信号是阶跃信号. 跟踪性能通过对象输出与参考信号之差的能量来衡量. 为了达到渐近跟踪, 提出了一个新的量化方案. 方案包括两部分: 一部分是在初始时刻将控制信号的稳态值通过网络传输给被控对象并且存储在其输入端; 另一部分则是通过对数量化器, 对控制信号的瞬态部分(即控制信号与其稳态值之差)进行量化, 然后传输给被控对象. 最后该量化信号与稳态控制信号相加后作用于被控对象. 这里, 假设对数量化误差是     

基于T-S模糊模型非线性网络控制系统改进H∞跟踪控制

研究一类非线性网络控制系统改进H∞跟踪控制问题, 该类网络控制系统中非线性被控对象和被跟踪对象分别采用Takagi-Sugeno(T-S)模糊模型和线性稳定参考模型描述. 首先通过综合考虑网络中的数据传输时滞和数据丢包影响, 采用输入时滞法和并行分布补偿技术, 建立基于零阶保持器刷新时刻的系统状态跟踪误差模型. 然后利用改进的自由权矩阵方法, 并结合Lyapunov直接法给出系统满足H∞跟踪性能的充分条件以及模糊控制器的设计方法. 最后仿真实例表明本文方法的有效性和相比已有方法的优越性.     

Optimal tracking performance of MIMO discrete‐time systems with communication constraints

The optimal tracking problem for multiple‐input multiple‐output linear‐time‐invariant discrete‐time systems with communication constraints in the feedback path is studied in this paper. The tracking performance is measured by the energy of the error signal between the output of the plant and the reference signal. The objective is to obtain an optimal tracking performance, attainable by all possible stabilizing compensators. It is shown that the optimal tracking performance consists of two parts, one depends on the nonminimum phase zeros and zero direction of the given plant, as well as the reference input signal direction, and the other depends on the nonminimum phase zeros, unstable poles, and pole direction of the given plant, as well as the bandwidth and additive white Gaussian noise of the communication channel. It is also shown that, if the constraint of the communication channel does not exist, the optimal tracking performance reduces to the existing tracking performance of the control system without communication constraints. A typical example is given to illustrate the theoretical results. Copyright © 2011 John Wiley & Sons, Ltd.     

大规模不一致传感网络环境带宽受限下的分布式状态估计

无线传感器网络环境下受限于能量和带宽,传感器的观测往往需要经过量化后才发送,针对大规模不一致传感网络环境且带宽受限下的分布式状态估计,探讨了量化比特分配和估计性能评估问题。首先给出一种二进制概率量化方案,并基于量化观测构造线性无偏量化估计器。然后,考虑一个总的传输比特率限制下,得到了传感器的最优量化比特率及比特分配方案,由其信噪比(SNR)和总带宽确定。同时,对提出的量化估计器的均方误差上界进行了分析,发现其与理论下界仅相差一个小常数因子。最后,仿真结果表明,相比于一般的均匀比特分配,文中所提出的最优比特分配方案估计性能更优。     

Best Tracking Performance of Networked Control Systems Based on Communication Constraints

The best tracking problem for a single‐input‐single‐output (SISO) networked control system with communication constraints is studied in this paper. The tracking performance is measured by the energy of the error signal between the output of the plant and the reference signal. The communication constraints under consideration are finite bandwidth and networked induced‐delay. Explicit expressions of the minimal tracking error have been obtained for networked control systems with or without communication constraints. It is shown that the best tracking performance dependents on the nonminimum phase zeros, and unstable poles of the given plant, as well as the bandwidth and networked induced‐delay. It is also shown that, if the constraints of the communication channel do not exist, the best tracking performance reduces to the existing tracking performance of the control system without communication constraints. The result shows how the bandwidth and networked induced‐delay of a communication channel may fundamentally constrain a control system's tracking capability. Some typical examples are given to illustrate the theoretical results.     

网络化系统周期信号的跟踪

研究线性时不变、单变量、离散网络化系统对周期信号的跟踪问题.与现有文献考虑的参考输入信号大都为常见的能量信号所不同的是,本文参考输入信号是离散时间周期方波功率信号.相应地,研究系统对基于功率谱的参考输入信号功率的响应,系统的跟踪性能通过输入信号与受控对象输出之差的功率来衡量,而最优跟踪性能采用跟踪误差的平均功率来度量.考虑的网络化控制系统仅上行通道存在丢包误差的影响,把丢包过程看作两个信号的合成,一是确定性信号,二是随机过程,进而丢包误差描述为源信号和白噪声之间乘积.根据被控对象和随机过程的性质,采用Parseval等式、维纳–辛钦定理和范数矩阵理论得到该系统跟踪性能极限的下界表达式.仿真结果表明,所设计的控制器能实现对周期信号的有效跟踪,进而验证了结论的正确性.     

Best tracking and regulation performance under control energy constraint

This paper studies optimal tracking and regulation control problems, in which objective functions of tracking error and regulated response, defined by integral square measures, are to be minimized jointly with the control effort, where the latter is measured by the plant input energy. Our primary objective in this work is to search for fundamental design limitations beyond those known to be imposed by nonminimum phase zeros, unstable poles, and time delays. For this purpose, we solve the problems explicitly by deriving analytical expressions for the best achievable performance. It is found that this performance limit depends not only on the plant nonminimum phase zeros, time delays, and unstable poles-a fact known previously-but also on the plant gain in the entire frequency range. The results thus reveal and quantify another source of fundamental performance limitations beyond those already known, which are nonexistent when only conventional performance objectives such as tracking and regulation are addressed without taking into account the control energy constraint. Among other things, they exhibit how the lightly damped poles, the anti-resonant zeros, as well as the bandwidth of the plant may affect the performance.     

基于宏块编码的MSE计算模型

在分析率失真理论的基础上,提出帧内编码宏块模式、帧间编码宏块模型的新思想,并建立均方差失真计算模型。该方法能够全局最优地求得在误码环境下,率失真曲线上的最佳控制点,不仅能够在给定的网络带宽下自适应地调整量化参数,而且可以根据当前网络丢包概率进行帧内宏块刷新,起到较好地抵抗信道误码的效果,对于无线环境中的视频鲁棒编码传输及资源分配,具有较好的参考价值。     

Implications of the degree of controllability of controlled plants in the sense of LQR optimal control

In this paper, the relationship between the degree of controllability (DOC) of controlled plants and the corresponding quadratic optimal performance index in LQR control is investigated for the electro-hydraulic synchronising servo control systems and wind turbine systems, respectively. It is shown that for these two types of systems, the higher the DOC of a controlled plant is, the better the quadratic optimal performance index is. It implies that in some LQR controller designs, the measure of the DOC of a controlled plant can be used as an index for the optimisation of adjustable plant parameters, by which the plant can be controlled more effectively.