602 research outputs found
Fault detection and fault-tolerant control for nonlinear systems
No full textLinlin Li addresses the analysis and design issues of observer-based FD and FTC for nonlinear systems. The author analyses the existence conditions for the nonlinear observer-based FD systems to gain a deeper insight into the construction of FD systems. Aided by the T-S fuzzy technique, she recommends different design schemes, among them the L_inf/L_2 type of FD systems. The derived FD and FTC approaches are verified by two benchmark processes. Contents Overview of FD and FTC Technology Configuration of Nonlinear Observer-Based FD Systems Design of L2 nonlinear Observer-Based FD Systems Design of Weighted Fuzzy Observer-Based FD Systems FTC Configurations for Nonlinear Systems< Application to Benchmark Processes Target Groups Researchers and students in the field of engineering with a focus on fault diagnosis and fault-tolerant control fields The Author Dr. Linlin Li completed her dissertation under the supervision of Prof. Steven X. Ding at the Faculty of Engineering, University of Duisburg-Essen, Germany
Using in situ and Satellite Hyperspectral Data to Estimate the Surface Suspended Sediments Concentrations in the Pearl River Estuary.pdf
No full textThe objectives of this study were to examine the effect of direct inoculation of seeds with the rhizobacteria Pseudomonas sp. SB on the growth of tall fescue and phytodegradation efficiency in an oily-sludge-contaminated soil. SB isolated from rhizosphere soil of tall fescue was evaluated for their plant-growth-promoting characters and ability to produce biosurfactant. A pot experiment was conducted to study the effect of inoculation of SB on phytoremediation. SB reduced the surface tension of culture media and produced indole acetic acid, siderophores, and 1-aminocyclopropane-1-carboxylate deaminase. Inoculation of SB increased shoot and root dry weights of tall fescue in oily-sludge-contaminated soil by 28 % and 19 %, respectively. Over 120 days, the content of total petroleum hydrocarbon in soil decreased by 33.9 %, 68.0 %, and 84.5 %, and of polycyclic aromatic hydrocarbons (PAHs) by 32.9 %, 40.9 %, and 46.2 %, respectively, in the no-plant control, tall fescue, and tall fescue + SB treatments. Inoculation of SB also increased the activity and biodiversity of soil microbial communities in the planted treatments. SB could produce biosurfactant and exhibited a number of characters of plant-growth-promoting rhizobacteria. Inoculation of SB to tall fescue led to more effective remediation of oily-sludge-contaminated soils.The objectives of this study were to examine the effect of direct inoculation of seeds with the rhizobacteria Pseudomonas sp. SB on the growth of tall fescue and phytodegradation efficiency in an oily-sludge-contaminated soil
On observer-based fault detection for nonlinear systems
No full textThis paper addresses analysis and integrated design of observer-based fault detection (FD) for nonlinear systems. To gain a deeper insight into the observer-based FD framework, definitions and existence conditions for nonlinear observer-based FD systems are studied first. Then, a scheme for an integrated design of observer-based FD systems for affine nonlinear systems is proposed. Our work is considerably inspired by the study on input-output stability and stabilization of nonlinear systems. Examples are given at the end of the paper to illustrate the theoretical results. (C) 2015 Elsevier B.V. All rights reserved.National Natural Science Foundation of China [61433001, 61174052, 61473004]SCI(E)[email protected]; [email protected]; [email protected]
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Navigation Instruction Validation Tool and Indoor Wayfinding Training System for People with Disabilities
No full textAccording to World Health Survey, there are 785 million (15.6%) people in the world that live with a disability. It is a well-known fact that lack of access to public transportation is a barrier for people with disabilities in seeking work or accessing health care. In this research, we seek to increase access to public transportation by introducing a virtual pre-travel training system that enables people with disabilities to get familiar with a public transportation venue prior to arriving at the venue. Using this system, users establish a mental map of the target environment prior to their arrival to the physical space, increasing their confidence and therefore increasing their chances of using public transportation. First, we have to guarantee that all navigation instructions sent to our training system are correct. Since the number of navigation instruction increases dramatically, instruction validation becomes a challenge. We propose a video game based validation tool which includes a game scene that represents in 2D the physical environment and uses a game avatar to verify the navigation instructions automatically in the game scene. The avatar traverses the virtual space following the corresponding navigation instructions. Only in case that it successfully reaches the planned destination, the current navigation instruction can be considered as correct. Then, we introduce a virtual reality based pre-travel wayfinding training system to assist people with disabilities to get familiar with a venue prior to their arrival at the physical space, which provides two modes: 1) Self-Guided mode in which the path between a source and a destination is shown to the user from third person perspective, and 2) Exploration mode in which the user explores and interacts with the environment. In the end, we have implemented visual analytics tools that track and evaluate trainees’ performance and help us optimize the game. These tools identify the difficulties faced by the trainees as well as obtain overall statistics on the trainees’ behavior in the indoor environment, helping us understand how to modify the system and adjust it to different classes of disabilities.Master of Science in Electrical and Computer Engineering (MSECE
Data-driven realizations of kernel and image representations and their application to fault detection and control system design
No full textThis paper deals with the data-driven design of observer-based fault detection and control systems. We first introduce the definitions of the data-driven forms of kernel and image representations. It is followed by the study of their identification. In the context of a fault-tolerant architecture, the design of observer-based fault detection, feed-forward and feedback control systems are addressed based on the data-driven realization of the kernel and image representations. Finally, the main results are demonstrated on the laboratory continuous stirred tank heater (CSTH) system. (C) 2014 Elsevier Ltd. All rights reserved.Automation & Control SystemsEngineering, Electrical & ElectronicSCI(E)[email protected]; [email protected]; [email protected]; [email protected]
A safety investment optimization model for power grid enterprises based on System Dynamics and Bayesian network theory
No full textIn recent years, frequent large-scale power grid accidents have caused serious economic losses and bad social impact, which has drawn great attention from power grid enterprises. As one of the key elements of production, safety investment plays an important role in improving the safety level and reducing accident loss. In this paper, System dynamics (SD) and Bayesian network (BN) are integrated to develop a novel safety investment optimization model for power grid enterprises, which takes into account the impact of safety investment factors on accidents and the interactions between them. Based on sensitivity analysis, critical safety investment factors are determined to form the subsystem of the SD model. Subsequently, the optimal safety investment strategy is determined by a three-step simulation. The simulation results show that there are barrel effects and a diminishing marginal utility in safety investment. The proposed safety investment optimization model is practical to provide technical supports and guidance for determining an effective safety investment strategy in power grid enterprises.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Safety and Security Scienc
Targeted Delivery of Macrophage Membrane Biomimetic Liposomes Through Intranasal Administration for Treatment of Ischemic Stroke
No full textTianshu Liu, Mengfan Zhang, Jin Zhang, Naijin Kang, Linlin Zheng, Zhiying Ding School of Pharmaceutical Sciences, Jilin University, Changchun, 130021, People’s Republic of ChinaCorrespondence: Zhiying Ding, School of Pharmaceutical Sciences, Jilin University, Changchun, 130021, People’s Republic of China, Tel/Fax +86 13843180286, Email [email protected]: Ginsenoside Rg3 (Rg3) and Panax notoginseng saponins (PNS) can be used for ischemic stroke treatment, however, the lack of targeting to the ischemic region limits the therapeutic effect. To address this, we leveraged the affinity of macrophage membrane proteins for inflamed brain microvascular endothelial cells to develop a macrophage membrane-cloaked liposome loaded with Rg3 and PNS (MM-Lip-Rg3/PNS), which can precisely target brain lesion region through intranasal administration.Methods: MM-Lip-Rg3/PNS was prepared by co-extrusion method and was performed by characterization, stability, surface protein, and morphology. The cellular uptake, immune escape ability, and blood-brain barrier crossing ability of MM-Lip-Rg3/PNS were studied in vitro. The in vivo brain targeting, biodistribution and anti-ischemic efficacy of MM-Lip-Rg3/PNS were evaluated in MACO rats, and we determined the diversity of the nasal brain pathway through the olfactory nerve blockade model in rats. Finally, the pharmacokinetics and brain targeting index of MM-Lip-Rg3/PNS were investigated.Results: Our results indicated that MM-Lip-Rg3/PNS was spherical with a shell-core structure. MM-Lip-Rg3/PNS can avoid mononuclear phagocytosis, actively bind to inflammatory endothelial cells, and have the ability to cross the blood-brain barrier. Moreover, MM-Lip-Rg3/PNS could specifically target ischemic sites, even microglia, increase the cumulative number of drugs in the brain, improve the inflammatory environment of the brain, and reduce the infarct size. By comparing olfactory nerve-blocking rats with normal rats, it was found that there are direct and indirect pathways for nasal entry into the brain. Pharmacokinetics demonstrated that MM-Lip-Rg3/PNS exhibited stronger brain targeting and prolonged drug half-life.Conclusion: MM-Lip-Rg3/PNS might contribute to the accumulation of Rg3 and PNS in the ischemic brain area to improve treatment efficacy. This biomimetic nano-drug delivery system provides a new and promising strategy for the treatment of ischemic stroke. Keywords: macrophage-membrane coating, biomimetic liposome, brain targeting, ischemic stroke, intranasal deliver
Parameterization of Nonlinear Observer-Based Fault Detection Systems
No full textThis note addresses parameterization issues of nonlinear observer-based fault detection (FD) systems which are composed of a residual generator, a residual evaluator and a threshold. Our study consists of two steps. In the first step, with the aid of nonlinear factorization and input-output operator techniques, we prove that any stable residual generator can be parameterized by a cascade connection of the process kernel representation and a post-filter that represents the parameter system. In the second step, based on the state-space representation of the parameterized residual generators, we investigate the so-called L-infinity- and L-2-classes of observer-based FD systems. This leads to the parameterization of the threshold settings for both classes of FD systems and, associated with them, to the characterization of the existence conditions.National Natural Science Foundation of China [61473004, 61433001, 61210012]SCI(E)[email protected]; [email protected]; [email protected]
A study on fault diagnosis in nonlinear dynamic systems with uncertainties
No full textIn this draft, fault diagnosis in nonlinear dynamic systems is addressed. The
objective of this work is to establish a framework, in which not only
model-based but also data-driven and machine learning based fault diagnosis
strategies can be uniformly handled. Instead of the well-established
input-output and the associated state space models, stable image and kernel
representations are adopted in our work as the basic process model forms. Based
on it, the nominal system dynamics can then be modelled as a lower-dimensional
manifold embedded in the process data space. To achieve a reliable fault
detection as a classification problem, projection technique is a capable tool.
For nonlinear dynamic systems, we propose to construct projection systems in
the well-established framework of Hamiltonian systems and by means of the
normalised image and kernel representations. For nonlinear dynamic systems,
process data form a non-Euclidean space. Consequently, the norm-based distance
defined in Hilbert space is not suitable to measure the distance from a data
vector to the manifold of the nominal dynamics. To deal with this issue, we
propose to use a Bregman divergence, a measure of difference between two points
in a space, as a solution. Moreover, for our purpose of achieving a
performance-oriented fault detection, the Bregman divergences adopted in our
work are defined by Hamiltonian functions. This scheme not only enables to
realise the performance-oriented fault detection, but also uncovers the
information geometric aspect of our work. The last part of our work is devoted
to the kernel representation based fault detection and uncertainty estimation
that can be equivalently used for fault estimation. It is demonstrated that the
projection onto the manifold of uncertainty data, together with the
correspondingly defined Bregman divergence, is also capable for fault
detection
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