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.     

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.     

编解码和时延约束下的网络化控制系统最优跟踪性能

本文研究了具有丢包、时延、编解码等通信资源受限下多输入多输出离散时间网络控制系统的最优跟踪性能. 基于频域方法, 采用二元随机过程来模拟数据包丢失, 并假设信道噪声是加性高斯白噪声(AWGN), 推导了在丢包、信道噪声、时延和编解码影响下的跟踪性能极限. 采用单参数补偿器(SDOF), 利用互质分解、Youla参数化等工具得到了编解码和时延约束下的网络控制系统最优跟踪性能的显式表达式. 结果表明, 跟踪性能与对象的固有特性(非最小相位零点与不稳定极点的位置和方向)、时延、丢包率和AWGN 功率谱密度密切相关.     

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.     

The problem of LQG optimal control via a limited capacity communication channel

The paper addresses a LQG optimal control problem involving bit-rate communication capacity constraints. A discrete-time partially observed system perturbed by white noises is studied. Unlike the classic LQG control theory, the control signal must be first encoded, then transmitted to the actuators over a digital communication channel with a given bandwidth, and finally decoded. Both the control law and the algorithms of encoding and decoding should be designed to archive the best performance. The optimal control strategy is obtained. It is shown that where the estimator-coder separation principle holds, the controller-coder one fails to be true.     

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.     

Optimal regulation performance of discrete time-delay systems based on quantization and input energy constraints

In this paper, we study the optimal regulation problem of networked control systems and propose a new performance index for a given discrete time-delay system. The regulation performance of the controlled plant is investigated by considering the effects of various constraints on the communication channel such as quantization, bandwidth, and packet dropouts using frequency domain methods and two-degree-of-freedom control techniques. The results show that the regulation performance is not only related to the location and direction of the non-minimum phase zeros and unstable poles of a given system but also related to the internal time delay of the controlled plant. Packet dropouts, quantization, and bandwidth limitations can also negatively affect the optimal performance. In addition, the trade-off of the input energy constraint can also make the optimal regulation performance suffer. Finally, the reliability of this innovative result is illustrated by some simulation examples.     

Modified performance of MIMO wireless networked time‐delay systems over fading channels

In this paper, the modified performance limitation of multi‐input multi‐output (MIMO) wireless networked time‐delay systems over fading channels is investigated, where the characteristic of the fading channels is assumed to be a random process. The modified tracking performance limitation is considered based on frequency domain representation. The display expressions of performance limitation are achieved by using the co‐prime factorization and the spectral decomposition techniques. The obtained results show that the modified performance limitation of the wireless networked time‐delay systems is related to the inherent characteristics of the given plant, including the non‐minimum phase zeroes, the unstable poles, the encoding‐decoding, the fading channels, the bandwidth and the modified factor. Finally, some numerical examples are provided to demonstrate the efficiency of the proposed design method.     

Try-once-discard scheduling for stochastic networked control systems

In practical networked control systems (NCS), such as smart grids, cooperative robotics, and sensor networks, often multiple control applications share a communication infrastructure, requiring a smart and efficient scheduling mechanism to coordinate the access to the capacity-limited communication medium. In this article we consider the problem of event-based scheduling design for NCSs consisting of multiple control loops over a shared communication medium. We extend the notion of Try-Once-Discard (TOD), which is one of the basic deterministic event-based scheduling protocols for resource constrained NCSs, to the case of multiple stochastic control systems coupled via a shared communication medium subject to capacity limitation and stochastic packet delivery failure. Showing that the overall network-induced error is a homogeneous Markov chain in our stochastic set-up, we first study stability properties of such networked systems under the TOD scheduling scheme employing the concepts of stochastic stability. Then, we derive sufficient stability conditions under the TOD rule assuming that the communication channel is not ideal, i.e. a scheduled data packet for transmission might be lost in the communication channel with a non-zero probability. Furthermore, we derive analytic performance bounds by finding uniform upper-bounds for an average quadratic cost function. The numerical simulations are performed for variety of system parameters and NCS set-ups to strengthen our stability claim as well as illustrating performance bounds. Additionally, we show that the TOD scheduling rule outperforms the conventional time-triggered, and uniform and non-uniform random channel access arbitration mechanisms, in terms of efficient coordination of channel access in stochastic NCSs.     

Event‐Triggered Iterative Learning Control for Multi‐Agent Systems with Quantization

The emergence of networked control systems urges the digital control design to integrate communication constraints efficiently. In order to accommodate this requirement, this paper investigates the joint design of tracking problem for multi‐agent system (MAS) in the presence of resource‐limited communication channel and quantization. An event‐triggered robust learning control with quantization is firstly proposed and employed for MAS in this paper. The new event‐triggered distributed robust learning control system with the introduction of logarithmic quantization guarantees the asymptotic tracking property on the finite interval. Convergence analysis is given based on the Lyapunov direct method. Finally, numerical simulations are given to illustrate the efficacy of the event‐triggered approach compared with time‐triggered controllers.     

基于置信传播算法的低密度校验码量化译码设计

介绍了二元输入连续输出无记忆AWGN信道下低密度校验 (LDPC)码的置信传播译码算法及其密度进化特性 .根据密度进化规律 ,分析了不同消息空间中的量化译码问题 .得出结论如下 :对于概率和概率差消息 ,只有高阶均匀量化才能获得满意的译码性能 ;似然比消息的适当对数量化可等价于对数似然比消息的均匀量化 ;对数似然比消息易于实现相对信道输入± 1的无偏对称量化 ,并有效利用消息的统计特性 .由非均匀量化在大消息区域分配的量化电平可以有效地促进算法收敛 .仿真结果表明 ,低阶非均匀量化优于均匀量化     

Architectures and coder design for networked control systems

In networked control systems (NCSs) achievable performance is limited by the communication links employed to transmit signals in the loop. In the present work, we characterise LTI coding systems which optimise performance for various NCS architectures. We study NCSs where the communication link is situated between plant output and controller, and NCSs where the communication link is located between controller and actuator. Furthermore, we present a novel NCS architecture, which is based upon the Youla parameterisation. We show that, which of these architectures gives best performance depends, inter alia, upon characteristics of a related non-networked design, plant disturbances and reference signal. A key aspect of our work, resides in the utilisation of fixed signal-to-noise ratio channel models which give rise to parsimonious designs, where channel utilisation is kept low. The results are verified with simulations utilising bit-rate limited channels.     

具有通信序列的网络控制系统LQG控制器设计

研究了具有通信序列的网络控制系统控制器设计问题.通过在系统的输入输出端设计通信序列,分时占用网络,以降低带宽约束对系统的影响,进而构建了具有通信序列的网络控制系统模型;在此基础上,将网络控制器设计分为2个部分,首先,基于输出值设计Kalman滤波器,用于提供最优状态估计值;然后,在考虑通信序列的基础上利用LQG方法协同...     

带事件触发机制的分布式量化随机无梯度投影算法

本文研究多智能体系统的分布式约束优化问题,系统中的每个智能体仅知道自身的局部目标函数和全局非空约束集,通过与邻居节点进行信息交互,最终协同求出优化问题的最优解.本文所提出的算法针对通信网络为时变不平衡有向图,且每个智能体不知道它的出度的情况.同时考虑到现实中通信带宽有限和通讯成本的限制,应用基于编译码方案的量化技术对节点之间的通讯信息进行预处理,再利用事件触发广播技术降低网络的通信次数.同时引入高斯光滑函数和随机无梯度方法替代传统的次梯度方法.本文提出了基于事件触发的分布式量化随机无梯度算法,在目标函数为凸且Lipschitz连续的条件下,证明了所提算法能收敛到最优值的邻域,同时给出了使量化器不饱和量化水平更新规则.最后通过数值仿真验证了算法的有效性和可行性.     

Performance Limitation of Networked Systems with Network‐Induced Delay and Packet‐Dropout Constraints

In this paper, we deeply investigate the tracking performance limitation of single‐input single‐output (SISO) networked systems with packet dropouts and network‐induced delay constrains, where the power of the tracking error is adopted to measure of the performance and is minimized by searching through all stabilizing one‐parameter controllers, with/without considering the channel input power. Moreover, the explicit expressions of the tracking performance limitation are obtained by applying the spectral factorization technique. Theoretical analysis shows that the tracking performance limitation is closely dependent on non‐minimum phase zeros, unstable poles of a given plant, the characteristics of the reference signals, network‐induced delay and packet dropouts probability of communication channel. Finally, some typical examples and simulations are conducted to illustrate the theoretical results.     

A Switched System Approach to Robust Stabilization of Networked Control Systems with Multiple Packet Transmission

This paper considers robust stabilization of networked control systems (NCSs) with the problem of multiple packet transmission. Two parts of uncertainties are considered in this paper: norm‐bounded parameter uncertainties in the plant, and norm‐bounded parameter uncertainties in the controller. For sensor nodes and actuator nodes communicating through a limited communication channel, we are particularly interested in the case that only one packet containing part of the state information can be transmitted through a toking‐bus every time. Stability of the NCSs with multiple packet transmitted in a periodic manner is closely related to that of periodically switched systems. For NCSs with and without uncertainties in the plant and the controller, stabilizing state feedback controllers are constructed in terms of linear matrix inequalities (LMIs). Numerical examples are given to illustrate the feasibility and effectiveness of the proposed approach.     

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.     

LQG-like control of scalar systems over communication channels: The role of data losses,delays and SNR limitations

In this work we address the problem of feedback control design for scalar systems in the presence of a non-ideal communication channel, which gives rise to tightly coupled limitations in terms of quantization errors, decoding/computational delays and packet loss affecting the closed loop control performance. We restrict our analysis to the context of LQG-like control, where the estimator and controller gains are forced to be constant, subject to SNR limitations, packet loss, and constant delay, and we derive their impact on the optimal design of the controller parameters. In particular, we show that the stability of the closed loop system depends on a tradeoff among SNR, packet loss probability and delay. Through this analysis we are also able to recover, as special cases, several results already available in the literature that have treated packet loss, quantization error and delay separately. We also show that the estimator and controller cannot be designed independently even if the controller has full knowledge of the packet loss sequence and the control inputs to the plant. In fact the optimal control gain, when accounting for the communication constraints is, in general, different from the optimal gain derived under the classical LQG scenario, which is recaptured when the SNR over the channel goes to infinity.     

资源约束网络的优化带宽调度

在资源约束的网络控制系统中, 控制性能和服务质量之间的折衷是不可避免的. 为了寻求它们的最佳结合点, 提出了结合约束条件的多目标规划问题来优化控制性能和网络带宽需求. 考虑算法的非线性逼近能力和计算速度, 采用了神经网络作为优化求解器. 它提供的优化解对每一个控制回路的带宽需求进行动态分配, 使得全局系统性能最大化的同时使带宽需求最小化. 仿真表明在网络控制应用中该优化策略对控制性能和网络带宽需求之间是一种有效的折衷方法.     

Iterative joint source-channel decoding of speech spectrum parameters over an additive white Gaussian noise channel

In this paper, we show how the Gaussian mixture modeling framework used to develop efficient source encoding schemes can be further exploited to model source statistics during channel decoding in an iterative framework to develop an effective joint source-channel decoding scheme. The joint probability density function (PDF) of successive source frames is modeled as a Gaussian mixture model (GMM). Based on previous work, the marginal source statistics provided by the GMM is used at the encoder to design a low-complexity memoryless source encoding scheme. The source encoding scheme has the specific advantage of providing good estimates to the probability of occurrence of a given source code-point based on the GMM. The proposed iterative decoding procedure works with any channel code whose decoder can implement the soft-output Viterbi algorithm that uses a priori information (APRI-SOVA) or the BCJR algorithm to provide extrinsic information on each source encoded bit. The source decoder uses the GMM model and the channel decoder output to provide a priori information back to the channel decoder. Decoding is done in an iterative manner by trading extrinsic information between the source and channel decoders. Experimental results showing improved decoding performance are provided in the application of speech spectrum parameter compression and communication.