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Institution

University of Macau

EducationMacao, Macau, China
About: University of Macau is a education organization based out in Macao, Macau, China. It is known for research contribution in the topics: Population & Control theory. The organization has 6636 authors who have published 18324 publications receiving 327384 citations. The organization is also known as: UM & UMAC.


Papers
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Journal ArticleDOI
TL;DR: A substructuring approach that allows for the identification and monitoring of some critical substructures only and allows one to obtain not only the most probable values of the updated model parameters but also their as- sociated uncertainties using only one set of response data is proposed.
Abstract: A probabilistic substructure identification and health monitoring methodology for linear systems is presented using measured response time histories only. A very large number of uncertain parameters have to be identified if one considers the updating of the entire structure. For identifiability, one then would require a very large number of sensors. Furthermore, even when such a large number of sensors are available, process- ing of vast amount of the corresponding data raises com- putational difficulties. In this article a substructuring ap- proach is proposed, which allows for the identification and monitoring of some critical substructures only. The proposed method does not require any interface measure- ments and/or excitation measurements. No information regarding the stochastic model of the input is required. Specifically, the method does not require the response to be stationary and does not assume any knowledge of the parametric form of the spectral density of the input. There- fore, the method has very wide applicability. The proposed approach allows one to obtain not only the most probable values of the updated model parameters but also their as- sociated uncertainties using only one set of response data. The probability of damage can be computed directly using data from the undamaged and possibly damaged struc- ture. A hundred-story building model is used to illustrate the proposed method.

105 citations

Journal ArticleDOI
TL;DR: An adaptive controller with redundancy resolution has been designed to drive the exoskeleton tracking the planned trajectory in human brain and to offer a convenient method of dynamics compensation with minimal knowledge of the dynamics parameters of theExoskeleton robot.
Abstract: In this paper, a closed-loop control has been developed for the exoskeleton robot system based on brain–machine interface (BMI). Adaptive controllers in joint space, a redundancy resolution method at the velocity level, and commands that generated from BMI in task space have been integrated effectively to make the robot perform manipulation tasks controlled by human operator’s electroencephalogram. By extracting the features from neural activity, the proposed intention decoding algorithm can generate the commands to control the exoskeleton robot. To achieve optimal motion, a redundancy resolution at the velocity level has been implemented through neural dynamics optimization. Considering human–robot interaction force as well as coupled dynamics during the exoskeleton operation, an adaptive controller with redundancy resolution has been designed to drive the exoskeleton tracking the planned trajectory in human brain and to offer a convenient method of dynamics compensation with minimal knowledge of the dynamics parameters of the exoskeleton robot. Extensive experiments which employed a few subjects have been carried out. In the experiments, subjects successfully fulfilled the given manipulation tasks with convergence of tracking errors, which verified that the proposed brain-controlled exoskeleton robot system is effective.

105 citations

Journal ArticleDOI
TL;DR: The superconvergent points of the traditional first-order Grunwald-Letnikov formula to approximate the Riemann-Liouville fractional derivatives are used to construct the several finite difference schemes for solving a class of time-fractional subdiffusion equations.

104 citations

Journal ArticleDOI
TL;DR: Multilayered semiconducting polymer nanoparticles are developed for in vivo imaging of lymph nodes and tumors with a high signal-to-noise ratio.
Abstract: Although organic semiconducting polymer nanoparticles (SPNs) have emerged as an important category of optical imaging agents, their application in molecular imaging is still in its infancy and faces many challenges. We herein report a straightforward one-pot synthetic approach to construct multilayered near-infrared (NIR) fluorescent SPNs with enhanced fluorescence and optimized biodistribution for in vivo molecular imaging. In addition to the SP core, the multilayered SPNs have a middle silica protection layer and an outer poly(ethylene glycol) (PEG) corona, which play crucial roles in enhancing the NIR fluorescence by up to ∼100 fold and reducing nonspecific interactions, respectively. Their proof-of-concept imaging applications are demonstrated in cells, zebrafish and living mice. The multilayered nanoarchitecture not only permits in vivo lymph node tracking with an ultrahigh signal-to-noise ratio (∼85), but also allows for more sensitive in vivo imaging of tumors with a fluorescence intensity ratio of tumor to liver that is ∼8-fold higher compared to that of the counterpart silica SPN. Thus, this study provides a simple yet effective nanoengineering approach to facilitate the application of SPNs in molecular imaging.

104 citations

Journal ArticleDOI
Qingsong Xu1
TL;DR: This paper presents the precision motion control of a piezoelectric nanopositioning stage using a new scheme of adaptive sliding mode control with uncertainty and disturbance estimation (ASMC-UDE), which is easy to realize because the hysteresis effect is not needed to be modeled.
Abstract: This paper presents the precision motion control of a piezoelectric nanopositioning stage using a new scheme of adaptive sliding mode control with uncertainty and disturbance estimation (ASMC-UDE). One uniqueness of the reported ASMC-UDE scheme is that an inherent chattering-free control action is guaranteed by eliminating the use of discontinuous control term. The reported ASMC-UDE strategy is easy to realize because the hysteresis effect is not needed to be modeled. Instead, the hysteresis is estimated and compensated by the robust control scheme. The control scheme is applicable to a system plant with either matched or unmatched disturbances. Unlike the existing UDE-based SMC control schemes, a reference model is not required by the proposed ASMC-UDE scheme. The stability of the chattering-free SMC strategy is proved in theory under the Lyapunov framework. The superiority of the presented control scheme over conventional approaches has been confirmed through comparative experimental studies. Moreover, the robustness of the controller in the presence of model disturbance and external disturbance has been verified.

104 citations


Authors

Showing all 6766 results

NameH-indexPapersCitations
Henry T. Lynch13392586270
Chu-Xia Deng12544457000
H. Vincent Poor109211667723
Peng Chen10391843415
George F. Gao10279382219
MengChu Zhou96112436969
Gang Li9348668181
Rob Law8171431002
Zongjin Li8063022103
Han-Ming Shen8023727410
Heng Li7974523385
Lionel M. Ni7546628770
C. L. Philip Chen7448220223
Chun-Su Yuan7239721089
Joao P. Hespanha7241839004
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202345
2022307
20212,579
20202,357
20192,075
20181,714