Optimal linear filtering for networked systems with communication constraints,fading measurements,and multiplicative noises

This paper is concerned with the filtering problem for discrete‐time networked systems with communication constraints, fading measurements, and multiplicative noises. The communication constraint is that, at each sampling instant, at most one of the various transmission nodes in the networked systems is permitted to access a shared communication channel, and then the received data are transmitted to a remote filter to perform the filtering task. The phenomenon of measurement fading appears in a random way when measurements are transmitted via the communication channel that undergoes slow fading. Using the innovation analysis approach and some results developed in this study, an optimal linear filter is proposed. The proposed optimal filter has a recursive structure and does not increase computation and storage load with time. Computer simulations are conducted to examine the performance of the proposed optimal filter. Copyright © 2016 John Wiley & Sons, Ltd.     

Fault‐tolerant control for wireless networked control systems with an integrated scheduler

This paper addresses a study of fault‐tolerant control (FTC) for wireless networked control systems (WNCSs) in industrial automatic processes. The WNCSs is composed of many subsystems, which operate with different sampling cycles. In order to meet the real‐time requirements and ensure a deterministic data transmission, the time division multiple access (TDMA) mechanism is adopted in WNCSs. The data in WNCSs are transmitted following a TDMA‐based scheduler. According to the periodicity, WNCSs integrated with the scheduler is first formulated as discrete linear time periodic systems (LTPSs). Afterwards, a fault estimation method for LTPSs is developed under a H_∞ performance specification with a regional pole constraint. With the achieved state observer and fault estimator, an FTC strategy for LTPSs is explored. Finally, the proposed methods are verified on a physical experimental WiNC platform. Copyright © 2016 John Wiley & Sons, Ltd.     

一类网络控制系统的建模与稳定性分析

针对一类具有不确定网络诱导时延和线性控制对象的网络控制系统,通过将网络诱导时延描述为一个常值再叠加一个不确定值的形式,重新描述了采样控制系统的数字控制器,将网络控制系统建模为一类具有不确定时延的连续时间系统.利用Lyapunov方法和线性矩阵不等式技术,推导出了闭环系统渐进稳定的充分条件.与已有的结果相比,所提出的算法具有更低的保守性,并通过一个数值算例验证了所提出算法的有效性.     

Traffic scheduling in distributed networked control systems with packet losses and delays for power systems voltage stabilization

In this paper, medium access control (MAC) sublayer data traffic scheduling in distributed networked control systems (DNCSs) with networked induced packet losses and delays is investigated for stabilization and control of system dynamics. An effective‐information‐directed distributed sensor selection algorithm is proposed to select sensors to participate in delay‐tolerant information filtering for state estimation. The distributed scheduling algorithm is based on the total amount of effective information for all measurements stored in the sensors. We consider packet loss in wireless networks as a special type of delay, so the impact of packet losses on effective information amount can also be studied for the formulation of distributed scheduling strategy in the presence of packet losses. The distributed data traffic scheduling considering packet losses and delays is carried out in a networked system with data packet dropout governed by a Markov process for voltage regulation and stabilization with distributed energy resources (DERs). Experimental results demonstrate that the scheduling algorithm with awareness of the system dynamic state can well control the power system dynamics. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

多路径的无线网络控制系统镇定性研究

研究了多路径传输环境下具有不确定时延的无线网络控制系统稳定性问题。首先采用了一种新方法把不同状态的网络时延信息分离出来,系统中传感器采用时间驱动,执行器和控制器均采用事件驱动方式。假设网络时延小于采样周期,利用不确定理论将无线网络控制系统建模为一类具有多时延的不确定线性离散系统;基于Lyapunov方法,给出了闭环系统稳定的充分条件,并采用线性矩阵不等式技术求出状态反馈控制律;仿真实例验证了该方法的正确性和有效性。     

A probabilistic approach to stability and stabilization of networked control systems

In this paper, a probabilistic approach is proposed to study the modeling, stability, and stabilization problems for networked control systems (NCSs) with simultaneous random network communication delay and data dropout. Different from existing modeling approaches, the proposed NCSs model naturally captures the stochastic characteristics of the considered NCSs by taking into account the effects of the random network communication delay and data dropout. Based on the developed NCSs model, necessary and sufficient conditions of stability analysis, state, and output feedback stabilization problems are tackled. Moreover, necessary and sufficient stability and stabilization conditions are also presented for the case when the occurrence probabilities of delay and data dropout are partially known. Finally, three numerical examples are provided to demonstrate the effectiveness and the reduced conservatism of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.     

Robust economic model predictive control of nonlinear networked control systems with communication delays

In this work, we consider economic model predictive control of nonlinear networked control systems subject to external disturbances and communication delays in both sensor-to-controller and controller-to-actuator channels. The problem is addressed in the framework of the min-max model predictive control. First, a delay compensation strategy is proposed to minimize the impact of communication delays on the control performance. In the compensation strategy, once the receiver at the controller node receives a new state measurement, the controller generates a control sequence and sends the sequence to the actuator to compensate for delayed control inputs. Subsequently, the presence of disturbance is explicitly considered for robustness and the semi-feedback min-max optimization algorithm is used to design the control law based on the estimate of the current state reconstructed by the estimator. Furthermore, the input-to-state practical stability of the proposed approach is established by constructing a modified Lyapunov function. Simulation results of a numerical example and a chemical process example demonstrate the applicability and effectiveness of our approach.     

Modeling and design of networked control systems using a stochastic switching systems approach

A networked control system (NCS) is a control system in which plants, sensors, controllers, and actuators are connected through communication networks. In this paper, we consider NCSs modeled by stochastic switching systems, and propose a new method for modeling and optimal control. First, a recursive representation of the expected value of the state is proposed. Next, after an over‐approximation of this recursive representation is derived, the optimal control problem is reduced to a linear programming problem. Finally, the effectiveness of the proposed method is shown by a numerical example. The proposed method provides us an easy‐to‐use control method for NCSs. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Fault detection for a class of nonlinear networked control systems

In this paper, an observer‐based fault detection (FD) method is presented for a class of nonlinear networked control systems (NCSs) with Markov transfer delays. Firstly, based on Euler approximate method, a nonlinear NCS model with uncertainty is proposed using the Takagi‐Sugeno (T‐S) fuzzy model. Some geometric conditions are given to transfer the NCS model into an output‐feedback form. Then, the H_∞ FD observer is designed such that the estimation error (residual) converges to zero, if there exist no fault and uncertainty in the system, or the residual is minimized in the sense of H_∞ norm, when system contains fault and uncertainties. Furthermore, to simplify the model, the approximate model without uncertainty is considered. Then, sufficient conditions for the existence of FD observer gain and the sampling time of NCSs are given to achieve the semiglobal practical property. An inverted pendulum example is used to illustrate the efficiency of the developed techniques. Copyright © 2009 John Wiley & Sons, Ltd.     

Fault estimation and accommodation for networked control systems with nonuniform sampling periods

This paper deals with the problem of fault estimation and accommodation for a class of networked control systems with nonuniform uncertain sampling periods. Firstly, the reason why the adaptive fault diagnosis observer cannot be applied to networked control systems is analyzed. Based on this analysis, a novel robust fault estimation observer is constructed to estimate both continuous‐time fault and system states by using nonuniformly discrete‐time sampled outputs. Furthermore, using the obtained states and fault information, a nonuniformly sampled‐data fault tolerant control law is designed to preserve the stability of the closed‐loop system. The proposed scheme can not only guarantee the impact of continuous‐time uncertainties and discrete‐time sampled estimation errors on the faulty system to satisfy a H _∞ performance index but also repress the negative effect of the unknown intersample behavior of continuous‐time fault by use of an inequality technique. Finally, simulation results are included to demonstrate the feasibility of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.     

Limits of control performance for distributed networked control systems in presence of communication delays

In terms of computational complexity and fault tolerance, distributed networked control systems (DNCSs) is favorable for large‐scale processes. However, it poses additional limitations on the achievable control performance, especially when communication delay is present. The conventional minimum variance (MV) benchmarks mainly consider the limitations caused by the system itself and can give overly estimates of achievable performance when applied to the systems under distributed networked control. This paper proposes a solution to the MV benchmark for DNCSs considering both system time delays and time‐invariant communication delays. Furthermore, lower and upper bounds of the MV benchmark are proposed to assess the performance of DNCSs when there are time‐varying communication delays. These results are useful for evaluating the potential performance improvement if a DNCS is implemented to replace a decentralized control system. The proposed results are illustrated by a simulation example.     

Robust weighted H∞ filtering for networked systems with intermittent measurements of multiple sensors

In this paper, we investigate the robust weighted H_∞ filtering problem for networked systems with intermittent measurements under the discrete‐time framework. Multiple outputs of the plant are measured by separate sensors, each of which has a specific failure rate. Network‐induced delay, packet dropouts and network‐induced disorder phenomena are all incorporated in the modeling of the network link. The resulting closed‐loop system involves both delayed noise and non‐delayed noise. In order to make full use of the delayed information, we define a weighted H_∞ performance index. Sufficient delay‐dependent and parameter‐dependent conditions for the existence of the filter and the solvability of the addressed problem are given via a set of linear matrix inequalities. Two simulation examples are presented to illustrate the relationship between the minimal performance level and the weighting factor, which show the effectiveness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.     

Hybrid online learning control in networked multiagent systems: A survey

This survey paper studies deterministic control systems that integrate three of the most active research areas during the last years: (1) online learning control systems, (2) distributed control of networked multiagent systems, and (3) hybrid dynamical systems (HDSs). The interest for these types of systems has been motivated mainly by two reasons: First, the development of cheap massive computational power and advanced communication technologies, which allows to carry out large computations in complex networked systems, and second, the recent development of a comprehensive theory for HDSs that allows to integrate continuous‐time dynamical systems and discrete‐time dynamical systems in a unified manner, thus providing a unifying modeling language for complex learning‐based control systems. In this paper, we aim to give a comprehensive survey of the current state of the art in the area of online learning control in multiagent systems, presenting an overview of the different types of problems that can be addressed, as well as the most representative control architectures found in the literature. These control architectures are modeled as HDSs, which include as special subsets continuous‐time dynamical systems and discrete‐time dynamical systems. We highlight the different advantages and limitations of the existing results as well as some interesting potential future directions and open problems.     

Robust fault tolerant control for a class of networked control systems with state delay and stochastic actuator failures

This paper is concerned with the robust fault tolerant controller design of networked control systems (NCSs) with state delay and stochastic actuator failures. By utilizing the input delay approach, an equivalent continuous‐time generalized time delay system in both state and input is obtained. By applying a delay decomposition approach, the information of the delayed plant states can be taken into full consideration, and new delay‐dependent sufficient conditions that ensure the asymptotic mean‐square stability of NCSs with stochastic actuator failures are derived in terms of linear matrix inequalities (LMIs). It is realized by employing a new Lyapunov–Krasovskii function in the decomposed integral intervals and directly handle the inversely weighted convex combination of quadratic terms of integral quantities with reciprocally convex combination technique. Moreover, the proposed approach involves neither slack variable nor any model transformation. A numerical example is provided to demonstrate the effectiveness and less conservatism of the proposed method.Copyright © 2012 John Wiley & Sons, Ltd.     

Fault detection for nonlinear networked systems with random packet dropout and probabilistic interval delay

In this paper, the fault detection (FD) problem of nonlinear networked control systems (NCSs) is investigated. A nonlinear stochastic systems model is proposed to account for the NCSs with network‐induced random packet dropout and non‐uniformly distributed time‐varying delay in both from sensor to controller and from controller to actuator. On the basis of the new model, by employing FD filter as residual generator, the addressed FD problem is converted into auxiliary nonlinear H _∞ filtering problem. Then, with the help of Lyapunov functional approach, a sufficient condition for the desired FD filter is constructed in terms of certain linear matrix inequalities, which depends on not only nonlinear level but also delay interval occurrence rate and successful joint packet transmission rate. Especially, a trade‐off phenomenon among maximum allowable delay bound, nonlinear level, and successful joint packet transmission rate is found, which typically resulted from the limited bandwidth of the communication networks. The effectiveness of the proposed methods is demonstrated by simulation examples. Copyright © 2011 John Wiley & Sons, Ltd.     

Finite‐time dissipativity‐based filter design for networked control systems

This paper investigates the problem of finite‐time boundedness and dissipativity‐based filter design for networked control systems together with parameter uncertainties and random packet dropouts. The packet transmission information is defined by using Bernoulli distributed white sequence which characterizes the measurement conditions. Some new sufficient conditions are established to ensure that the filtering error system is stochastically finite‐time bounded and strictly finite‐time dissipative. These sufficient conditions to design the filter parameters are derived by using linear matrix inequalities and reciprocally convex approach. Finally, an example is given to validate the effectiveness of the proposed filter design.     

一种变采样周期的网络控制系统控制与调度协同设计新方法

针对存在时变时延与随机丢包的变采样周期网络控制系统,提出了一种鲁棒控制与采样周期调度协同设计方法。运用模糊控制中的最大隶属度解模糊方法,依据系统误差大小使得采样周期在几个固定值之间切换。根据采样周期计算出满足性能指标的状态反馈矩阵K,并按照当前的采样周期选择相对应的K来计算控制量。可以避免由同时考虑时变采样周期与时变时延所带来的强保守性。设计鲁棒控制器时采用Markov 链描述系统随机丢包,使得建模更贴近实际情况,运用标称点法确定由时延组成的系统不确定项的范数界,可以进一步减小保守性。最后,数值仿真结果验证了该协同设计方法的可行性与有效性。     

存在信道噪声和随机丢包的多机器人协调控制

针对无线网络环境下存在信道噪声和Markov型随机丢包的多机器人协调控制进行研究.假设机器人之间的通信拓扑是固定不变的,将机器人之间的连接权重、网络中的信道噪声和Markov型随机丢包等不确定因素转化为不确定系统中的某些不确定参数.依据鲁棒控制理论、不确定系统理论,建立多机器人系统模型.通过对整个系统的稳定性进行分析,采用线性矩阵不等式的求解方法,得到使多个机器人能够达到状态一致的权重选择条件,并设计出保持系统稳定的一致协调控制算法.利用可模拟网络环境下系统运行的仿真软件,分析多个机器人的运动状态特性曲线,并与参考文献中的类似问题进行比较,验证了所提算法的有效性.     

网络直流伺服电机滑模预测控制

利用滑模变结构控制方法对存在丢包情况下的网络直流伺服电机控制系统的鲁棒性问题进行了研究.对于控制器和执行器之间网络存在数据丢包的情况,设计了基于滑模预测控制律的网络丢包补偿模型,包括滑模预测控制产生器和丢包预测补偿器2个部分.研究了相应的动态补偿策略,使在每一时刻系统选取的实际控制量都是执行器端所提供的最新控制信号或最...     

具有非线性扰动的网络化随机系统鲁棒控制

针对具有非线性扰动的网络化随机系统的鲁棒控制问题,考虑到反馈控制环中由于实时通讯网络的存在会不可避免地出现网络诱导时延和数据丢失现象,建立了连续时间网络化随机系统模型.在此基础上,设计了状态反馈控制器,使得闭环系统最终均方有界.利用广义系统变换和Lyapunov-Krasovskii泛函方法,得到了闭环系统最终均方有界的充分条件,证明了理想的状态反馈控制器可以通过求解线性矩阵不等式得到.该方法可推广到以双线性随机系统为受控对象的网络化控制系统的镇定控制器设计中.