Evaluation of fault diagnosability for networked control systems subject to missing measurements   总被引：1，自引：0，他引：1  

Fangzhou Fu  Dayi Wang  Ping Liu  Wenbo Li 《Journal of The Franklin Institute》2018,355(17):8766-8779

The evaluation of fault diagnosability for networked control systems subject to missing measurements is addressed in this paper. In particular, the missing probability is assumed to be affected by norm-bounded uncertainties. By considering noise and missing measurements, the quantitative diagnosability problem is investigated via the principle of weight. To quantify the effect of uncertain missing probabilities, an interval criterion is presented and uncertainty ratio is defined. Furthermore, a novel method is proposed to alleviate the computation task of evaluating fault diagnosability. The effectiveness of the proposed method is verified by a numerical example.  相似文献   

Semi-global leader-following coordination of multi-agent systems with input saturation and aperiodic intermittent communications     

Zhipeng Fan  Housheng Su  Shiming Chen  Minghui Yu  Jie Ma 《Journal of The Franklin Institute》2019,356(2):1051-1066

This paper addresses the semi-global leader-following coordination problem of general linear multi-agent systems, in which the control input of each agent is steered by aperiodically intermittent saturated actuator. Both the case with only one virtual leader and the case with multiple virtual leaders are discussed. By using multiple Lyapunov stability theory and applying algebraic Riccati equation-based low-gain feedback technique, sufficient conditions guaranteeing semi-global consensus tracking and semi-global containment tracking are provided. Numerical simulations finally verify the theoretical analysis.  相似文献   

Stabilization of switched linear singular systems with state reset     

Xiaoqing Xiao  Ju H. Park  Lei Zhou 《Journal of The Franklin Institute》2019,356(1):237-247

This paper investigates the stability and stabilization of switched linear singular systems with state reset at switching instants. Based on the dynamics decomposition of singular subsystems, a sufficient stability condition for the system with the given state reset is obtained. Then, the stabilization problem by state reset is investigated and an algorithm for computing the reset matrices is presented. The obtained results extend some previous works on both singular switched systems and reset control for normal switched systems. Finally, a numerical example is presented to illustrate the effectiveness of the proposed approach.  相似文献   

Observer-based decentralized control of large-scale stochastic high-order feedforward systems with multi time delays     

Liang Liu  Shengyuan Xu  Xue-Jun Xie  Bing Xiao 《Journal of The Franklin Institute》2019,356(16):9627-9645

This paper investigates the problem of observer-based decentralized control for a class of large-scale stochastic high-order feedforward systems with multi time delays. By using the homogeneous domination idea and constructing the implementable observer, the decentralized output-feedback controller design scheme is firstly proposed. Then, with the aid of stochastic time delay system stability theory, the globally asymptotically stable in probability of the closed-loop system is verified by selecting an appropriate Lyapunov–Krasoviskii functional. Finally, an example is provided to demonstrate the efficiency of the proposed design method.  相似文献   

Stabilization for a class of rectangular descriptor systems via time delayed dynamic compensator     

Chong Lin  Jian Chen  Bing Chen  Lei Guo  Qing-Guo Wang  Ziye Zhang 《Journal of The Franklin Institute》2019,356(4):1944-1954

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Fixed-time outer synchronization of hybrid-coupled delayed complex networks via periodically semi-intermittent control     

Qintao Gan  Feng Xiao  Hui Sheng 《Journal of The Franklin Institute》2019,356(12):6656-6677

In this paper, the fixed-time synchronization between two delayed complex networks with hybrid couplings is investigated. The internal delay, transmission coupling delay and self-feedback coupling delay are all included in the network model. By introducing and proving a new and important differential equality, and utilizing periodically semi-intermittent control, some fixed-time synchronization criteria are derived in which the settling time function is bounded for any initial values. It is shown that the control rate, network size and node dimension heavily influence the estimating for the upper bound of the convergence time of synchronization state. Finally, numerical simulations are performed to show the feasibility and effectiveness of the control methodology by comparing with the corresponding finite-time synchronization problem.  相似文献   

Centralized security-guaranteed filtering in multirate-sensor fusion under deception attacks     

Zidong Wang  Dong Wang  Bo Shen  Fuad E. Alsaadi 《Journal of The Franklin Institute》2018,355(1):406-420

In this paper, the centralized security-guaranteed filtering problem is studied for linear time-invariant stochastic systems with multirate-sensor fusion under deception attacks. The underlying system includes a number of sensor nodes with a centralized filter, where each sensor is allowed to be sampled at different rate. A new measurement output model is proposed to characterize both the multiple rates and the deception attacks. By exploiting the lifting technique, the multi-rate sensor system is cast into a single-rate discrete-time system. With a new concept of security level, the aim of this paper is to design a filter such that the filtering error dynamics achieves the prescribed level of the security under deception attacks. By using the stochastic analysis techniques, sufficient conditions are first derived such that the filtering error system is guaranteed to have the desired security level, and then the filter gain is parameterized by using the semi-definite programme method with certain nonlinear constraints. Finally, a numerical simulation example is provided to demonstrate the feasibility of the proposed filtering scheme.  相似文献   

Mixed ℓ₂ and ℓ₁-norm regularization for adaptive detrending with ARMA modeling     

L. Giarré  F. Argenti 《Journal of The Franklin Institute》2018,355(3):1493-1511

In this paper, the problem of detrending a time series and/or estimating a wandering baseline is addressed. We propose a new methodology that adaptively minimizes different regularized cost functions by introducing an ARMA model of the underlying trend. Mixed ?₁/?₂-norm penalty functions are taken into consideration and novel RLS and LMS solutions are derived for the model parameters estimation. The proposed methods are applied to typical trend estimation/removal problems that can be found in the analysis of economic time series or biomedical signal acquisition. Comparisons with standard noncausal filtering techniques are also presented.  相似文献   

Adaptive fault-tolerant control for continuous-time Markovian jump systems with signal quantization     

Dongyang Zhao  Yu Liu  Ming Liu  Jinyong Yu  Yan Shi 《Journal of The Franklin Institute》2018,355(6):2987-3009

This paper investigates the adaptive fault-tolerant control problem for a class of continuous-time Markovian jump systems with digital communication constraints, parameter uncertainty, disturbance and actuator faults. In this study, the exact information for actuator fault, disturbance and the unparametrisable time-varying stuck fault are totally unknown. The dynamical uniform quantizer is utilized to perform the design work and the mismatched initializations at the coder and decoder sides are also considered. In this paper, a novel quantized adaptive fault-tolerant control design method is proposed to eliminate the effects of actuator fault, parameter uncertainty and disturbance. Moreover, it can be proved that the solutions of the overall closed-loop system are uniformly bounded, which is asymptotically stable almost surely. Finally, numerical examples are provided to verify the effectiveness of the new methodology.  相似文献   

A neural network-based detection and mitigation system for unintended acceleration     

Reza Langari 《Journal of The Franklin Institute》2018,355(10):4315-4335

Modern vehicles are equipped with a growing number of electronic devices, which significantly improve the driving experience. However, the complicated architecture of electronic systems also increases the difficulty of fault diagnosis since process models are often unavailable. This paper presents a novel detection and mitigation system for vehicle related anomalies originating in unintended acceleration (UA), which has become one of the most complained-about vehicle problems in recent history. The detection system consists of several neural network-based models, which are created by analyzing historical vehicle data at specific moments such as acceleration peaks and gear shifting. These data-driven models describe the boundary of normal vehicle behavior in the data space. A priori knowledge of complete vehicle structures is not necessary for building them. The detection system combines these models to decide if a UA event has occurred. When a UA event is detected, a mitigation system cuts the engine power and adjusts the braking force accordingly. The whole system was validated in the Simulink/dSPACE environment. UA errors were simulated so that they occurred randomly when human subjects drove virtual cars in a simulated environment. Random noise of sensors were also considered and incorporated to add realism. Various traffic scenarios were included in tests. Test results show that the integrated system is capable of detecting UA in one second with high accuracy and reducing the risk of accidents.  相似文献