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Conceptual design of compliant mechanisms using level set method

Shi-kui CHEN, Michael Yu WANG

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 2, Pages 131-145 doi: 10.1007/s11465-006-0018-y

Abstract: one-higher dimensional level set function, and the dynamic variations of the shape are governed by the Hamilton-JacobiBy making a connection between the velocity field in the Hamilton-Jacobi partial differential equation

Keywords： splitting minimum dimensional optimization Hamilton-Jacobi topological

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Galerkin approximationwith Legendre polynomials for a continuous-time nonlinear optimal control problem Article

Xue-song CHEN

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10, Pages 1479-1487 doi: 10.1631/FITEE.1601101

Abstract: The approach derived from the Galerkin approximation is used to solve the generalized Hamilton-Jacobi-Bellman

Keywords： Generalized Hamilton-Jacobi-Bellman equation Nonlinear optimal control Galerkin approximation Legendre

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Indirect adaptive fuzzy-regulated optimal control for unknown continuous-time nonlinear systems

Haiyun Zhang, Deyuan Meng, Jin Wang, Guodong Lu,gray_sun@zju.edu.cn,tinydreams@126.com,dwjcom@zju.edu.cn,lugd@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 2, Pages 141-286 doi: 10.1631/FITEE.1900610

Abstract: Initially, the Hamilton-Jacobi-Bellman (HJB) equation associated with its performance function is derived

Keywords： Indirect adaptive optimal control Hamilton-Jacobi-Bellman equation Fuzzy-regulated critic Adaptive

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Modal disturbance investigation of rod-shaped ultrasonic motor using bending vibrations

ZHANG Jiantao, ZHU Hua, ZHAO Chunsheng

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 3, Pages 343-347 doi: 10.1007/s11465-008-0058-6

Abstract: a dynamic analysis model of a stator is created on the basis of the finite element method (FEM) and Hamilton

Keywords： Hamilton principle disturbance separation frequency separation dynamic analysis

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Phase synchronization and energy balance between neurons Research Article

Ying XIE, Zhao YAO, Jun MA

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 9, Pages 1407-1420 doi: 10.1631/FITEE.2100563

Abstract: A functional neuron has been developed from a simple by incorporating a phototube and a thermistor in different branch circuits. The physical field energy is controlled by the photocurrent across the phototube and the channel current across the thermistor. The firing mode of this neuron is controlled synchronously by external temperature and illumination. There is energy diversity when two functional neurons are exposed to different illumination and temperature conditions. As a result, synapse connections can be created and activated in an adaptive way when field energy is exchanged between neurons. We propose two kinds of criteria to discuss the enhancement of synapse connections to neurons. The energy diversity between neurons determines the increase of the coupling intensity and synaptic current for neurons, and the realization of synchronization is helpful in maintaining energy balance between neurons. The first criterion is similar to the saturation gain scheme in that the coupling intensity is increased with a constant step within a certain period until it reaches energy balance or complete synchronization. The second criterion is that the coupling intensity increases exponentially before reaching energy balance. When two neurons become non-identical, phase synchronization can be controlled during the activation of synapse connections to neurons. For two identical neurons, the second criterion for taming synaptic intensity is effective for reaching complete synchronization and energy balance, even in the presence of noise. This indicates that a synapse connection may prefer to enhance its coupling intensity exponentially. These results are helpful in discovering why synapses are awaken and synaptic current becomes time-varying when any neurons are excited by external stimuli. The potential biophysical mechanism is that energy balance is broken and then synapse connections are activated to maintain an adaptive energy balance between the neurons. These results provide guidance for designing and training intelligent neural networks by taming the coupling channels with gradient energy distribution.

Keywords： Hamilton energy Coupling synchronization Synapse enhancement Neural circuit