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Power Control in Wireless Body Area Networks: A Review of Mechanisms, Challenges, and Future Directions. [PDF]

Sensors (Basel)
Su H, Zhao Z, Gu B, Lin S.
europepmc   +1 more source

The Mechanism and Design Principles of Serious Games in Enhancing Adolescents' Internet Adaptability.

JMIR Serious Games
Gao S, Jia M, Wang W, Hu J, Ma S.
europepmc   +1 more source

Iterative learning control for performance optimisation

Chu, Bing
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Intermittent iterative learning control

2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006
In this paper we present a mathematical formulation of the problem of robust iterative learning control (ILC) design when the system is subject to data dropout. It is assumed that an ILC scheme is implemented via a networked control system (NCS) and that during the data transfer from the remote plant to the ILC controller data dropout occurs, resulting
Hyo-sung Ahn, Yangquan Chen, Kevin Moore
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Event-Triggered Nonlinear Iterative Learning Control

IEEE Transactions on Neural Networks and Learning Systems, 2021
An event-triggered nonlinear iterative learning control (ET-NILC) method is presented for repetitive nonaffine and nonlinear systems that have 2-D dynamic behavior along both time and iteration directions. Based on the virtual linear data model, the ET-NILC method is proposed by designing an event triggering condition based on the Lyapunov-like ...
Na Lin, Ronghu Chi, Biao Huang, Zhongsheng Hou   +3 more
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Predictive Iterative Learning Control

Intelligent Automation & Soft Computing, 2003
There are applications in which the control system is commanded to execute identical and repetitive tasks. These include pick-and-place robot control, moulding control, and many semiconductor processes. The iterative learning control (ILC) method first introduced by Arimoto et al. (1984) is based on the previous control history and a learning mechanism.
S. N. Huang, S. Y. Lim
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Iterative Identification of Feedforward Controllers for Iterative Learning Control

IFAC Proceedings Volumes, 2009
Abstract One the the main disadvantages to the standard iterative learning control (ILC) problem is that the learning filter is static and does not update based on the current iteration information. This means that while the learning control is updating the feedforward control input, the learning controller itself is not updating.
Hoday Stearns, Benjamin Fine, Masayoshi Tomizuka   +2 more
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Robust gradient-based Iterative Learning Control

2007 International Workshop on Multidimensional (nD) Systems, 2007
This paper considers the robustness of a gradient-based Iterative Learning Control (ILC) algorithm to ensure monotonic convergence with respect to the mean square value of the error time series. The paper provides necessary and sufficient conditions for robust monotonic convergence and sufficient frequency domain conditions for robust monotonic ...
D.H. Owens, J. Hatonen, S. Daley
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Parameter optimisation in iterative learning control

2003 European Control Conference (ECC), 2003
In this paper parameter optimization through a quadratic performance index is introduced as a method to establish a new iterative learning control law. With this new algorithm, monotonic convergence of the error to zero is guaranteed if the original system is a discrete-time LTI system and it satisfies a positivity condition.
D. H. Owens, K. Feng
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