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 detection filter design for networked control systems with time‐varying sampling periods and packet dropouts

This paper investigates the problem of fault detection for networked control systems under simultaneous consideration of time‐varying sampling periods and packet dropouts. By taking time‐varying sampling periods into consideration, a new closed‐loop model for the considered networked control systems is established. The sampling period switching‐based approach and the parameter uncertainty‐based approach are adopted to deal with time‐varying sampling periods. Based on the established model, the observer‐based fault detection filter design criteria are proposed to asymptotically stabilize the residual system in the sense of mean‐square. The designed observer‐based fault detection filter can guarantee the sensitivity of the residual signal to faults. The simulation results illustrate the effectiveness of the obtain results. Copyright © 2015 John Wiley & Sons, Ltd.     

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。     

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.     

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.     

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.     

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.     

Fault diagnosis and fault-tolerant control of uncertain network control systems

In this article, the equivalent control strategy based on Laplace transform is proposed for the problem of stochastic delay in networked control systems. The original system is transformed into an equivalent control system without random delay block by Laplace transform. Then, a new augmented variable and equivalent control system is introduced to construct an augmented system. An adaptive fault diagnosis observer is designed based on the augmented system. The adaptive turning rate of the observer is obtained by solving the corresponding linear matrix inequality. Based on the information of online fault diagnosis and state estimation, a fault-tolerant controller based on PI control strategy is designed to compensate the fault. Finally, a model of the switched reluctance motor system is considered to show the effectiveness of this method.     

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.     

Less conservative criteria for fault accommodation of time‐varying delay systems using adaptive fault diagnosis observer

This paper studies the problem of fault accommodation of time‐varying delay systems using adaptive fault diagnosis observer. Based on the proposed fast adaptive fault estimation (FAFE) algorithm using only a measured output, a delay‐dependent criteria is first established to reduce the conservatism of the design procedure, and the FAFE algorithm can enhance the performance of fault estimation. On the basis of fault estimation, the observer‐based fault‐tolerant tracking control is then designed to guarantee tracking performance of the closed‐loop systems. Furthermore, comprehensive analysis is presented to discuss the calculation steps using linear matrix inequality technique. Finally, simulation results of a stirred tank reactor model are presented to illustrate the efficiency of the proposed techniques. Copyright © 2009 John Wiley & Sons, Ltd.     

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.     

Optimal filtering and control for wireless networked closed-loop control systems

This article studies the optimal filtering and control for wireless networked control systems (WNCSs). In WNCSs, packets may be lost in both control and feedback channels and user datagram protocol is usually used to improve the performance of the real-time control. Relevant literature indicates that the conventional optimal filtering for such a system cannot be applied in practice due to the complex calculation with Gaussian mixtures. This paper proposes a novel scheme to realize the optimal filtering and the linear quadratic Gaussian control for WNCSs, in which the controlled node performs a local estimation and the remote-control node performs the final estimation and control, and a synchronization of two estimators is guaranteed by a communication mechanism. An optimal filtering algorithm is developed, the stability condition of the filtering error covariance is obtained, optimal finite-horizon and infinite-horizon control are derived, and the stability of the closed-loop control system is proved. Numerical simulations show the validity and feasibility of the theoretical results.     

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.     

一种并行交替采样中时基非均匀信号自适应重构方法

并行采集系统中,通道间时基延迟的不一致性严重降低了系统性能。通过对系统时基误差分量的分析,提出了一种基于自适应控制的非均匀信号重构方法。该方法不需要额外增加校准信号,能在误差估计的同时自动完成信号重构,实时性高;无需重构滤波器,降低了系统设计难度及成本。实验结果表明,经过约250次自适应迭代后,该重构算法能有效估计通道时基误差,具有迭代次数少、运算量小、能动态跟踪时基延迟变化的特点;重构后系统信噪比由原来的33dB提高到48dB,有效位数提高近2.5bit,系统性能得到了大幅提高。     

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.     

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.     

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.     

Fault accommodation for multi‐input linear sampled‐data systems

A novel observer‐based fault accommodation technique for linear multi‐input multi‐output sampled‐data systems affected by a general class of actuator faults in the presence of quantization errors is addressed in the paper. Only the output signal has been assumed to be available for direct measurement. A simulation study on a three‐tank system supports theoretical developments. Copyright © 2014 John Wiley & Sons, Ltd.     

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.     

Adaptive fault-tolerant tracking control for nonlinear systems with unknown control coefficient and input saturation

In this article, the tracking control problem is investigated for a class of nonlinear systems in the presence of unknown disturbance, input saturation, actuator fault, and unknown control coefficient. A novel disturbance observer-based adaptive fault-tolerant tracking control strategy is proposed with regard to nonlinear systems. Based on the Gaussian error function, the auxiliary dynamic system is designed to offset effects caused by the input saturation. Moreover, the Nussbaum-type function is employed to avert control singularity and deal with the unknown control coefficient. A theoretical analysis indicates that the boundedness of all signals in the closed-loop system can be guaranteed. Finally, two examples with one concerning the dynamic point-the-bit rotary steerable drilling tool system are given to confirm the validity of the method.