scholarly journals Adaptive Feedback Control in Human Reaching Adaptation to Force Fields

2021 ◽  
Vol 15 ◽  
Author(s):  
James Mathew ◽  
Frédéric Crevecoeur
Keyword(s):  
Feedback Control ◽  
Computational Models ◽  
Force Fields ◽  
Feedback Control System ◽  
Short Term ◽  
Central Function ◽  
Adaptive Feedback ◽  
Adaptive Feedback Control ◽  
Short Term Adaptation ◽  
And Control

Sensorimotor adaptation is a central function of the nervous system, as it allows humans and other animals to flexibly anticipate their interaction with the environment. In the context of human reaching adaptation to force fields, studies have traditionally separated feedforward (FF) and feedback (FB) processes involved in the improvement of behavior. Here, we review computational models of FF adaptation to force fields and discuss them in light of recent evidence highlighting a clear involvement of feedback control. Instead of a model in which FF and FB mechanisms adapt in parallel, we discuss how online adaptation in the feedback control system can explain both trial-by-trial adaptation and improvements in online motor corrections. Importantly, this computational model combines sensorimotor control and short-term adaptation in a single framework, offering novel perspectives for our understanding of human reaching adaptation and control.

Adaptive Control of a Simulated MEMS Gyroscope

2003 ◽  
Author(s):  
Qais A. Khasawneh ◽  
C. Batur
Keyword(s):  
Stability Control ◽  
Low Power Consumption ◽  
Mems Devices ◽  
Feedback Control System ◽  
Micro Electro Mechanical Systems ◽  
Adaptive Feedback ◽  
Lumped Model ◽  
Adaptive Feedback Control ◽  
The Stability ◽  
And Control

Micro Electro Mechanical Systems (MEMS) are playing a significant role in industry because of their small size, small weight, and low power consumption. The vibrating gyroscope is one of those MEMS devices that will have significant impact in stability control of cars. This paper studies the design and control of a vibrating gyroscope. The device has been constructed in Pro-E environment and its model has been simulated in finite element domain in order to approximate its dynamic characteristics with a lumped model. An adaptive feedback control system that guarantees the stability of the device and consistent measurement of angular velocity has been constructed and simulated.

Open-loop adaptive feedback control of deposited zinc in hot-dip galvanizing

1993 ◽  
Vol 1 (5) ◽  
pp. 779-790 ◽  
Author(s):  
C. Fenot ◽  
F. Rolland ◽  
G. Vigneron ◽  
I.D. Landau
Keyword(s):  
Feedback Control ◽  
Open Loop ◽  
Adaptive Feedback ◽  
Adaptive Feedback Control

Adaptive Feedback Control of Nonholonomic Systems with Uncertainties

2014 ◽  
Vol 971-973 ◽  
pp. 337-340
Author(s):  
Gui Ling Ju ◽  
Wei Hai Sun ◽  
Jian Du ◽  
Yun Chang Hang
Keyword(s):  
Feedback Control ◽  
Nonholonomic Systems ◽  
The State ◽  
Output Measurement ◽  
Adaptive Feedback ◽  
Adaptive Feedback Control ◽  
Strongly Nonlinear ◽  
Output Feedback Controller ◽  
Nonlinear Uncertainties ◽  
Switching Control Strategy

This paper deals with the adaptive feedback control for the nonholonomic systems with strongly nonlinear uncertainties. The state-input scaling technique and back-stepping approach are used to design the output feedback controller. In order to make the state scaling effective, a new switching control strategy based on the output measurement of the first subsystem is employed.

scholarly journals Adaptive Feedback Control for Synchronization of Chaotic Neural Systems with Parameter Mismatches

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Qian Ye ◽  
Zhengxian Jiang ◽  
Tiane Chen
Keyword(s):  
Feedback Control ◽  
Invariance Principle ◽  
Neural Systems ◽  
Adaptive Feedback ◽  
Adaptive Feedback Control ◽  
Synchronization Problem ◽  
Feedback Method

This work pertains to the study of the synchronization problem of a class of coupled chaotic neural systems with parameter mismatches. By means of an invariance principle, a rigorous adaptive feedback method is explored for synchronization of a class of coupled chaotic delayed neural systems in the presence of parameter mismatches. Finally, the performance is illustrated with simulations in a two-order neural systems.

Adaptive feedback control of ultrafast semiconductor nonlinearities

2000 ◽  
Vol 77 (7) ◽  
pp. 924 ◽  
Author(s):  
J. Kunde ◽  
B. Baumann ◽  
S. Arlt ◽  
F. Morier-Genoud ◽  
U. Siegner ◽  
...  
Keyword(s):  
Feedback Control ◽  
Adaptive Feedback ◽  
Adaptive Feedback Control

scholarly journals Adaptive stochastic synchronization of delayed reaction–diffusion neural networks

2020 ◽  
Vol 53 (3-4) ◽  
pp. 378-389 ◽  
Author(s):  
Weiyuan Zhang ◽  
Junmin Li ◽  
Jinghan Sun ◽  
Minglai Chen
Keyword(s):  
Neural Networks ◽  
Feedback Control ◽  
Sufficient Conditions ◽  
Reaction Diffusion ◽  
Linear Matrix ◽  
Output Coupling ◽  
Delayed Reaction ◽  
Adaptive Feedback ◽  
Adaptive Feedback Control ◽  
Stochastic Synchronization

In this paper, we deal with the adaptive stochastic synchronization for a class of delayed reaction–diffusion neural networks. By combing Lyapunov–Krasovskii functional, drive-response concept, the adaptive feedback control scheme, and linear matrix inequality method, we derive some sufficient conditions in terms of linear matrix inequalities ensuring the stochastic synchronization of the addressed neural networks. The output coupling with delay feedback and the update laws of parameters for adaptive feedback control are proposed, which will be of significance in the real application. The novel Lyapunov–Krasovskii functional to be constructed is more general. The derived results depend on the measure of the space, diffusion effects, and the upper bound of derivative of time-delay. Finally, an illustrated example is presented to show the effectiveness and feasibility of the proposed scheme.

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