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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 novel event-triggered adaptive control scheme is developed, which ensures that partial states are without violation of required constraints and the tracking error converges to a small neighborhood of the origin despite appearing as saturated phenomenon.
Abstract: This paper investigates the problem of event-triggered adaptive control for a class of nonlinear systems subject to asymmetric input saturation and time-varying partial state constraints. To facilitate analyzing the influence of asymmetric input saturation, the saturation function is converted into a linear form with respect to control input. To achieve the objective that partial states do not exceed the constraints, a more general form of Lyapunov function is offered. Different from some existing results about output/full state constraints, the proposed scheme only requires that the partial states satisfy the time-varying constraints. Moreover, an event-triggered scheme with a varying threshold is designed to reduce the communication burden. With the time-varying asymmetric barrier Lyapunov functions, a novel event-triggered control scheme is developed, which ensures that partial states are without violation of required constraints and the tracking error converges to a small neighborhood of the origin despite appearing as saturated phenomenon. Eventually, the theoretic results are confirmed by two examples.

148 citations

Journal ArticleDOI
TL;DR: This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form and proposes two neural-network-based adaptive control algorithms.
Abstract: This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form. Compared with previous works on the hysteresis phenomenon, the direction of the modified Bouc–Wen hysteresis model investigated in the literature is unknown. To reduce the computation burden in adaptation mechanism, an optimized adaptation method is successfully applied to the control design. Based on the Lyapunov–Krasovskii method, two neural-network-based adaptive control algorithms are constructed to guarantee that all the system states and adaptive parameters remain bounded, and the tracking error converges to an adjustable neighborhood of the origin. In final, some numerical examples are provided to validate the effectiveness of the proposed control methods.

148 citations

Journal ArticleDOI
TL;DR: The reusability of immobilized laccase makes it more advantageous in the practical applications of water purification, in comparison with free laccases, and this review is expected to provide a valuable guideline for enzymatic water purifying.

148 citations

Journal ArticleDOI
TL;DR: To fully exploit the potential of PCHM in cancer therapy, more attentions are advocated to be focused on their safety evaluation and mechanism exploration.

147 citations

Journal ArticleDOI
TL;DR: Study design quality has not improved over the last decade, indicating a need for greater consistency and standardization in this area, and continuing international efforts to understand the core psychopathology of gaming disorder are vital to developing a model of best practice in treatment.

147 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