Robust fault-tolerant control for networked control systems subject to random delays via static-output feedback

This paper focuses on the problem of fault-tolerant controller (FTC) design for uncertain networked control systems (NCSs) with random delays and actuator faults. A new fault model is proposed to represent more class of actuator faults. More precisely, the NCSs with random delays and the possible actuator faults are modeled as a Markovian jump system (MJS) with incomplete transition probabilities (TPs) and then LMI-based sufficient conditions are derived to ensure the stochastic stability of the closed-loop system. The sufficient conditions are constructed to synthesize the mode-dependent static-output feedback (SOF) control laws. Feasibility and reliability of the proposed FTC against actuator faults are indicated through simulation results.     

Design of robust reliable control for T-S fuzzy Markovian jumping delayed neutral type neural networks with probabilistic actuator faults and leakage delays: An event-triggered communication scheme

This study examines the problem of robust reliable control for Takagi-Sugeno (T-S) fuzzy Markovian jumping delayed neural networks with probabilistic actuator faults and leakage terms. An event-triggered communication scheme. First, the randomly occurring actuator faults and their failures rates are governed by two sets of unrelated random variables satisfying certain probabilistic failures of every actuator, new type of distribution based event triggered fault model is proposed, which utilize the effect of transmission delay. Second, Takagi-Sugeno (T-S) fuzzy model is adopted for the neural networks and the randomness of actuators failures is modeled in a Markov jump model framework. Third, to guarantee the considered closed-loop system is exponential mean square stable with a prescribed reliable control performance, a Markov jump event-triggered scheme is designed in this paper, which is the main purpose of our study. Fourth, by constructing appropriate Lyapunov-Krasovskii functional, employing Newton-Leibniz formulation and integral inequalities, several delay-dependent criteria for the solvability of the addressed problem are derived. The obtained stability criteria are stated in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Finally, numerical examples are given to illustrate the effectiveness and reduced conservatism of the proposed results over the existing ones, among them one example was supported by real-life application of the benchmark problem.     

One-step receding horizon H(∞) control for networked control systems with random delay and packet disordering

The receding horizon H(∞) control (RHHC) problem is investigated in this paper for a class of networked control systems (NCSs) with random delay and packet disordering. A new model is proposed to describe the NCS with random delay which may be larger than one sampling period. The random delay is modeled as a Markov chain while the closed-loop system is described as a Markovian jump system. Sufficient conditions for the closed-loop NCS to be stochastically stable and the performance index to be upper bounded are derived by using the receding optimization principle. Furthermore, by solving a semi-definite programming (SDP) with linear matrix inequalities (LMIs) constraint, a piecewise-constant receding horizon H(∞) controller is obtained, and the designed piecewise-constant controller ensures that the closed-loop NCS achieves a prescribed H(∞) disturbance attenuation level. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method.     

Actuator fault estimation and accommodation for switched systems with time delay: Discrete-time case

This paper investigates the problems of actuator fault estimation and accommodation for discrete-time switched systems with state delay. By using reduced-order observer method and switched Lyapunov function technique, a fault estimation algorithm is achieved for the discrete-time switched system with actuator fault and state delay. Then based on the obtained online fault estimation information, a switched dynamic output feedback controller is employed to compensate for the effect of faults by stabilizing the closed-loop systems. Finally, an example is proposed to illustrate the obtained results.     

Guaranteed cost control of mobile sensor networks with Markov switching topologies

This paper investigates the consensus seeking problem of mobile sensor networks (MSNs) with random switching topologies. The network communication topologies are composed of a set of directed graphs (or digraph) with a spanning tree. The switching of topologies is governed by a Markov chain. The consensus seeking problem is addressed by introducing a global topology-aware linear quadratic (LQ) cost as the performance measure. By state transformation, the consensus problem is transformed to the stabilization of a Markovian jump system with guaranteed cost. A sufficient condition for global mean-square consensus is derived in the context of stochastic stability analysis of Markovian jump systems. A computational algorithm is given to synchronously calculate both the sub-optimal consensus controller gains and the sub-minimum upper bound of the cost. The effectiveness of the proposed design method is illustrated by three numerical examples.     

Robust guaranteed cost control for singular Markovian jump systems with time-varying delay

This paper is concerned with the guaranteed cost control for continuous-time singular Markovian jump systems with time-varying delay. Without using the free weighting matrices method, a delay-range-dependent condition is derived in terms of strict linear matrix inequality (LMI), which guarantees that the singular system is regular, impulse free and mean-square exponentially stable with an H(∞) performance. Based on this, the existence condition of the guaranteed cost state feedback controller is proposed. A numerical example is given to illustrate the effectiveness and less conservatism of the proposed design method.     

Distributed fault-tolerant model predictive control for intermittent fault: A cooperative way

For intermittent actuator faults of large-scale system, a cooperative distributed fault-tolerant model predictive control (DFTMPC) is presented. The actuator plug and play strategy is adopted in the interconnected systems with physical coupling making fault estimation and controller redesign unnecessary. The actuator plug and play process is modeled as a distributed switching model, and there a theoretical stability analysis is provided with switching form of model predictive control (MPC) cost functions. The novel cooperative distributed fault-tolerant performance index is raised in a global view for distributed model predictive control. A simulation example is taken to show the e?ectiveness of the proposed method.     

基于神经网络的余度舵机系统故障诊断

对复杂的余度舵机系统进行故障诊断对提高飞行控制系统的可靠性和容错能力具有重要意义。文章提出1种变结构径向基神经网络学习算法,使用梯度下降法对网络参数进行优化,利用径向基神经网络对某型飞机余度舵机系统进行故障模式识别。仿真结果表明设计的神经网络具有较强的故障模式识别能力。     

往复压缩机气量调节控制失稳自愈调控方法研究

针对往复压缩机无级气量调节常见的调控失稳故障，构建包含压缩机、管道、缓冲罐、执行机构等部件的无级气量调节多系统耦合控制模型，仿真往复压缩机无级气量调节动态特性。以控制系统输出的脉宽调制控制信号作为输入，以压缩机各级排气压力作为输出，研究执行机构动态响应和控制系统调控参数对气量调节结果影响的规律；进一步针对执行机构性能参数变化导致气量调节控制失稳的问题，利用BP神经网络构建多参数负荷动态反馈模型实现调控失稳故障诊断和故障类型识别。基于故障异常类型识别结果提出一种调控参数自适应优化补偿的自愈调控方法。试验结果表明，提出的自愈调控方法可在失稳故障发生后主动施加调控参数补偿量，使得气量调节系统恢复到正常状态，实现故障在线自愈。     

Optimal production control and marketing plan in two-machine unreliable flexible manufacturing systems

In this paper, we have developed a production planning and marketing model in unreliable flexible manufacturing systems with inconstant demand rate that its rate depends on the level of advertisement on that product. The proposed model is more realistic and useful from a practical point of view. The flexible manufacturing system is composed of two machines that produce a single product. Markovian models frequently have been used in modeling a wide variety of real-world systems under uncertainties. Therefore, in this paper, the inventory balance equation is represented by a continuous-time model with Markov jump process to take into account machines breakdown. The objective is to minimize the expected total cost of the firm over an infinite time horizon. While the total cost consists of the cost of the product surplus, the cost of the production, and the cost of the advertisement. In the process of finding a solution to the problem, we first characterize an optimal control by a class of linear stochastic system where some parameter values are subject to random jump. By defining quadratic cost functions and characterizing the associated limiting optimal control problem, a discrete-time approximation model and an asymptotic optimal control model are developed. It is clear that such a solution exists and can be obtained as a limit of a monotonic sequence with solving the steady-state Riccati equation.     

Robust adaptive fault-tolerant control for leader-follower flocking of uncertain multi-agent systems with actuator failure

In this work, we study the flocking problem of multi-agent systems with uncertain dynamics subject to actuator failure and external disturbances. By considering some standard assumptions, we propose a robust adaptive fault tolerant protocol for compensating of the actuator bias fault, the partial loss of actuator effectiveness fault, the model uncertainties, and external disturbances. Under the designed protocol, velocity convergence of agents to that of virtual leader is guaranteed while the connectivity preservation of network and collision avoidance among agents are ensured as well.     

捆扎线缆束电磁耦合效应限值模型研究

捆扎线缆束中线缆间的串扰研究是复杂电子系统电磁兼容预测分析的关键。提出了一种预测随机捆扎线缆束中线线耦合的限值模型,并设计了针对性试验进行验证。仿真结果与试验结果吻合良好,证明了限值模型的正确性和有效性。     

A bounded-error approach to actuator fault diagnosis and remaining useful life prognosis of Takagi-Sugeno fuzzy systems

The paper presents an actuator fault diagnosis and prognosis scheme for Takagi-Sugeno fuzzy system. It overcomes the drawbacks of the approaches presented in the relevant literature by taking into consideration the problem of the robustness. The proposed approach consists of an actuator fault estimator which provides knowledge about faults with their uncertainty intervals. Thus, the fault detection mechanism relies on an acceptable threshold imposed on these intervals. Once the fault is detected, the remaining useful life of an actuator is predicted what is expressed in the so-called time-to-failure. Similarly as in the case of fault estimation, the remaining useful life is provided as an uncertainty interval. It should be notated that previously reported approaches to Takagi-Sugeno systems cannot either provide the uncertainty of fault estimates for remaining useful life. To tackle the development of the above schemes the theory of quadratic boundedness and feasible parameter set-based estimation are employed. The final part of the paper portrays a case study which clearly exhibits the performance of the proposed approach.     

基于随机投影和NB网络的模拟电路故障诊断

针对模拟电路故障诊断中故障类型复杂多样、典型故障信息难以获取以及易受噪声、温度等环境影响的难题,提出一种基于随机投影和朴素贝叶斯网络的模拟电路故障诊断方法。该方法首先提取模拟电路故障信息,并利用随机投影算法降维后获取模拟电路故障特征向量,然后通过朴素贝叶斯分类器诊断模型识别模拟电路各个故障。通过对CSTV滤波器电路、四运放双二次高通滤波器电路和实际Sallen-Key带通滤波器电路的实验结果分析表明,相对于传统的模拟电路故障诊断方法,该方法表现出更优的故障诊断性能,并具有更强的抗干扰能力。     

State and actuator fault estimation observer design integrated in a riderless bicycle stabilization system

This paper deals with an observer design for Linear Parameter Varying (LPV) systems with high-order time-varying parameter dependency. The proposed design, considered as the main contribution of this paper, corresponds to an observer for the estimation of the actuator fault and the system state, considering measurement noise at the system outputs. The observer gains are computed by considering the extension of linear systems theory to polynomial LPV systems, in such a way that the observer reaches the characteristics of LPV systems. As a result, the actuator fault estimation is ready to be used in a Fault Tolerant Control scheme, where the estimated state with reduced noise should be used to generate the control law. The effectiveness of the proposed methodology has been tested using a riderless bicycle model with dependency on the translational velocity v, where the control objective corresponds to the system stabilization towards the upright position despite the variation of v along the closed-loop system trajectories.     

Robust fault detection for nonlinear networked systems with stochastic interval delay characteristics

In this paper, the problem of observer-based robust fault detection (RFD) for nonlinear networked systems with stochastic interval delay is investigated. By employing the information of probabilistic distribution of networked-induced time-varying delay, the observer-based fault detection filter as residual generator and a proposed performance index as objective function, the RFD of nonlinear networked systems is formulated as an optimization problem. The desired fault detection filter is constructed in terms of certain linear matrix inequalities, which depend on not only delay-interval but also delay-interval-occurrence-rate. Especially, the sub-optimal trade-off of strong robustness from residual signal to disturbance and parameter uncertainty, as well as high sensitivity to fault is obtained by a repeated application of a two-objective optimization algorithm. Numerical simulations are given to illustrate the effectiveness of proposed techniques.     

非线性系统的集成故障诊断和容错控制

基于解析模型而建立的状态观测法是一种得到了广泛应用的故障诊断和容错控制方法,而该方法在非线性不确定系统中的实际应用却由于未知输入扰动的影响受到一定的局限.针对机电系统中常见的严格反馈型不确定非线性系统,并考虑含有未知输入扰动,提出一种集成故障诊断与容错控制的设计方案,使系统在对不确定模型具有鲁棒性的同时,对执行器故障具有较强的跟踪性.该方案给出一种基于滑模变结构的容错控制器设计方法,并利用滑模变结构中的等值控制方法设计状态观测器,利用自适应方法实现对不同形式故障的重构.将所提方法以电液伺服系统为例进行仿真分析.仿真结果表明,系统对不确定模型具有鲁棒性,对突变、缓变和间歇变化等3种常见形式的故障以及带噪声的缓变故障均可进行较好的重构.     

贝叶斯网络理论及其在设备故障诊断中的应用

在分析机电设备故障诊断技术中广泛存在的不确定性和复杂关联关系的基础上，指出目前的故障诊断方法在处理不确定性和关联性问题时存在的局限性，提出了应用基于概率理论和图论的贝叶斯网络作为设备故障诊断模型具有很好前景的观点。阐述了贝叶斯网络的提出与发展、模型数学描述及研究现状，讨论了贝叶斯网络在故障诊断领域应用的可能方式及其应用情况。指出贝叶斯网络技术在故障诊断领域中的应用将进一步得到推广，提出了将贝叶斯网络广泛应用到故障诊断领域中需要解决的关键技术。