29,339 research outputs found
Robust Fault Detection of Switched Linear Systems with State Delays
This correspondence deals with the problem of robust fault detection for discrete-time switched systems with state delays under an arbitrary switching signal. The fault detection filter is used as the residual generator, in which the filter parameters are dependent on the system mode. Attention is focused on designing the robust fault detection filter such that, for unknown inputs, control inputs, and model uncertainties, the estimation error between the residuals and faults is minimized. The problem of robust fault detection is converted into an H infin-filtering problem. By a switched Lyapunov functional approach, a sufficient condition for the solvability of this problem is established in terms of linear matrix inequalities. A numerical example is provided to demonstrate the effectiveness of the proposed method
KV-match: A Subsequence Matching Approach Supporting Normalization and Time Warping [Extended Version]
The volume of time series data has exploded due to the popularity of new
applications, such as data center management and IoT. Subsequence matching is a
fundamental task in mining time series data. All index-based approaches only
consider raw subsequence matching (RSM) and do not support subsequence
normalization. UCR Suite can deal with normalized subsequence match problem
(NSM), but it needs to scan full time series. In this paper, we propose a novel
problem, named constrained normalized subsequence matching problem (cNSM),
which adds some constraints to NSM problem. The cNSM problem provides a knob to
flexibly control the degree of offset shifting and amplitude scaling, which
enables users to build the index to process the query. We propose a new index
structure, KV-index, and the matching algorithm, KV-match. With a single index,
our approach can support both RSM and cNSM problems under either ED or DTW
distance. KV-index is a key-value structure, which can be easily implemented on
local files or HBase tables. To support the query of arbitrary lengths, we
extend KV-match to KV-match, which utilizes multiple varied-length
indexes to process the query. We conduct extensive experiments on synthetic and
real-world datasets. The results verify the effectiveness and efficiency of our
approach.Comment: 13 page
Generalized Anthropomorphic Functional Grasping with Minimal Demonstrations
This article investigates the challenge of achieving functional tool-use
grasping with high-DoF anthropomorphic hands, with the aim of enabling
anthropomorphic hands to perform tasks that require human-like manipulation and
tool-use. However, accomplishing human-like grasping in real robots present
many challenges, including obtaining diverse functional grasps for a wide
variety of objects, handling generalization ability for kinematically diverse
robot hands and precisely completing object shapes from a single-view
perception. To tackle these challenges, we propose a six-step grasp synthesis
algorithm based on fine-grained contact modeling that generates physically
plausible and human-like functional grasps for category-level objects with
minimal human demonstrations. With the contact-based optimization and learned
dense shape correspondence, the proposed algorithm is adaptable to various
objects in same category and a board range of robot hand models. To further
demonstrate the robustness of the framework, over 10K functional grasps are
synthesized to train our neural network, named DexFG-Net, which generates
diverse sets of human-like functional grasps based on the reconstructed object
model produced by a shape completion module. The proposed framework is
extensively validated in simulation and on a real robot platform. Simulation
experiments demonstrate that our method outperforms baseline methods by a large
margin in terms of grasp functionality and success rate. Real robot experiments
show that our method achieved an overall success rate of 79\% and 68\% for
tool-use grasp on 3-D printed and real test objects, respectively, using a
5-Finger Schunk Hand. The experimental results indicate a step towards
human-like grasping with anthropomorphic hands.Comment: 20 pages, 23 figures and 7 table
Control of spiral waves and turbulent states in a cardiac model by travelling-wave perturbations
We propose a travelling-wave perturbation method to control the
spatiotemporal dynamics in a cardiac model. It is numerically demonstrated that
the method can successfully suppress the wave instability (alternans in action
potential duration) in the one-dimensional case and convert spiral waves and
turbulent states to the normal travelling wave states in the two-dimensional
case. An experimental scheme is suggested which may provide a new design for a
cardiac defibrillator.Comment: 9 pages, 5 figure
Kernel Truncated Regression Representation for Robust Subspace Clustering
Subspace clustering aims to group data points into multiple clusters of which
each corresponds to one subspace. Most existing subspace clustering approaches
assume that input data lie on linear subspaces. In practice, however, this
assumption usually does not hold. To achieve nonlinear subspace clustering, we
propose a novel method, called kernel truncated regression representation. Our
method consists of the following four steps: 1) projecting the input data into
a hidden space, where each data point can be linearly represented by other data
points; 2) calculating the linear representation coefficients of the data
representations in the hidden space; 3) truncating the trivial coefficients to
achieve robustness and block-diagonality; and 4) executing the graph cutting
operation on the coefficient matrix by solving a graph Laplacian problem. Our
method has the advantages of a closed-form solution and the capacity of
clustering data points that lie on nonlinear subspaces. The first advantage
makes our method efficient in handling large-scale datasets, and the second one
enables the proposed method to conquer the nonlinear subspace clustering
challenge. Extensive experiments on six benchmarks demonstrate the
effectiveness and the efficiency of the proposed method in comparison with
current state-of-the-art approaches.Comment: 14 page
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