An improved diagnosis method of technological systems is proposed in this paper that is based on their qualitative colored Petri-net model (Leitold et al. 2014). The proposed diagnosis method can be used when more tha...
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ISBN:
(纸本)9789077381953
An improved diagnosis method of technological systems is proposed in this paper that is based on their qualitative colored Petri-net model (Leitold et al. 2014). The proposed diagnosis method can be used when more than one fault occur in the system and if the fault evolves during the operation of the system. In order to make the diagnosis of complex process systems computationally feasible, a structural decomposition method is introduced to reduce the size of their occurrence graphs and to make the diagnosis easier. The proposed methods are illustrated on examples.
The classical ant colony algorithm for vehicle routing problem with time windows (VRPTW) has problems of low efficiency, slow convergence and prematurity. And the discrete ant colony optimization (DACO) is proposed fo...
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This paper investigates the asymptotic stability of a class of switched linear time-invariant discrete-time systems. Without the restriction of switching signals, a novel result is first proposed to guarantee uniform ...
Cyber-physical systems(CPSs) are integrations of networks, computation and physical processes, where embedded computing devices continually sense, monitor, and control the physical processes through networks. Networke...
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Cyber-physical systems(CPSs) are integrations of networks, computation and physical processes, where embedded computing devices continually sense, monitor, and control the physical processes through networks. Networked industrial processes combining internet, real-time computercontrol systems and industrial processes together are typical CPSs. With the increasingly frequent cyber-attack, security issues have gradually become key problems for CPSs. In this paper, a cyber-physical system security protection approach for networked industrial processes, i.e., industrial CPSs, is proposed. In this approach, attacks are handled layer by layer from general information technology(IT) security protection, to active protection, then to intrusion tolerance and physical security protection. The intrusion tolerance implemented in real-time control systems is the most critical layer because the real time control system directly affects the physical layer. This novel intrusion tolerance scheme with a closed loop defense framework takes into account the special requirements of industrial CPSs. To illustrate the effectiveness of the CPS security protection approach, a networked water level control system is described as a case study in the architecture analysis and design language(AADL) environment. Simulation results show that 3 types of injected attacks can be quickly defended by using the proposed protection approach.
This paper deals with event-triggering based design of discrete-time sliding mode (DTSM) control for linear systems. Multirate output feedback based DTSM is designed with event-triggering strategy such that the system...
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This paper deals with event-triggering based design of discrete-time sliding mode (DTSM) control for linear systems. Multirate output feedback based DTSM is designed with event-triggering strategy such that the system trajectories remain bounded in the vicinity of sliding manifold. An event-triggering rule is developed for DTSM which is evaluated only at periodic time intervals. The control is updated whenever the triggering instant is generated at these discrete time instants. It is shown that with this technique the system trajectories remain bounded. Also, in this triggering scheme there is always guaranteed Zeno free execution of triggering sequences as it is inherently discrete. Simulation results are shown to demonstrate the theoretical treatments of this paper.
The paper presents an event-triggering based sliding mode control law for delta operator systems with disturbance. The discrete domain representation of a system using shift operator becomes numerically ill-conditione...
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The paper presents an event-triggering based sliding mode control law for delta operator systems with disturbance. The discrete domain representation of a system using shift operator becomes numerically ill-conditioned at very high sampling rates. To circumvent this problem, the system is represented using delta operator. The delta operator creates a rapprochement between continuous-time and discrete-time system model at very high sampling rates. A discrete-time sliding mode (DTSM) control law is developed to achieve robustness against external disturbances. Further to reduce the resource utilization, an event-triggered DTSM control law is proposed such that the closed loop system is stable. Due to the inherent discrete nature of the control there is no accumulation of triggering instants at any instant of time. Hence the zeno free execution of the control updating instants is always guaranteed. Simulation results are also shown to illustrate the effectiveness of the proposed method.
This paper presents a 0.65-V flipped voltage follower (FVF)-based regulator with an embedded sub-1-V voltage reference. A low-pass filter is employed in the current coupling path to reduce the bias noise and improve t...
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ISBN:
(纸本)9781509004911
This paper presents a 0.65-V flipped voltage follower (FVF)-based regulator with an embedded sub-1-V voltage reference. A low-pass filter is employed in the current coupling path to reduce the bias noise and improve the power supply rejection (PSR) at a low-frequency band (
The major challenge in printable electronics fabrication is to effectively and accurately control a drop-on-demand(Do D) inkjet printhead for high printing quality. In this work, an optimal prediction model, construct...
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The major challenge in printable electronics fabrication is to effectively and accurately control a drop-on-demand(Do D) inkjet printhead for high printing quality. In this work, an optimal prediction model, constructed with the lumped element modeling(LEM) and the artificial bee colony(ABC) algorithm, was proposed to efficiently predict the combination of waveform parameters for obtaining the desired droplet properties. For acquiring higher simulation accuracy, a modified dynamic lumped element model(DLEM) was proposed with time-varying equivalent circuits, which can characterize the nonlinear behaviors of piezoelectric printhead. The proposed method was then applied to investigate the influences of various waveform parameters on droplet volume and velocity of nano-silver ink, and to predict the printing quality using nano-silver ink. Experimental results show that, compared with two-dimension manual search, the proposed optimal prediction model perform efficiently and accurately in searching the appropriate combination of waveform parameters for printable electronics fabrication.
One largest problem for tracking-by-detection methods is the incomplete and noisy training set. Occlusion, illumination and many other problems could lead to this problem. Models that are not adaptive enough would fai...
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ISBN:
(纸本)9781467389600
One largest problem for tracking-by-detection methods is the incomplete and noisy training set. Occlusion, illumination and many other problems could lead to this problem. Models that are not adaptive enough would fail to track the target when drastic appearance change takes place. Adaptive ones, although keep tracking at first, could lose the target because of learning too many incorrect samples. In this paper, we present an ensemble model of random classifiers updated on different dataset. When the appearance of the target changes drastically and some sub-models are confused, the others could help correct the tracking result. A latent variable is added for choosing sub-models and it naturally leads to predicting the new samples with a weighted sum of sub-models. To calculate the weight, we add a generative model to each random classifier. Experiments show that our method could track the target robustly and accurately.
In this paper, we propose a new role analyzing paradigm for social networks enlightened by topic modeling, which can be adopted as a primitive building block in various security related tasks, such as hidden community...
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ISBN:
(纸本)9781509038664
In this paper, we propose a new role analyzing paradigm for social networks enlightened by topic modeling, which can be adopted as a primitive building block in various security related tasks, such as hidden community finding, important person recognizing and so on. We first present the social network under analyzing as a heterogeneous network constructed by both the users and the subjects discussed among them. We then view this network in a Bag-of-Users schema, which mimics its classical Bag-of-Words counterpart. In this schema, the subjects discussed are treated as “documents” while the users are treated as “words” which construct the “documents”. Based on this novel presentation, we finally apply topic modeling technology to perform the social role clustering. Experiments on a practical security-related social network dataset prove the effectiveness of our approach.
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