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» Reducing input parameter uncertainty for simulations
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ISCAS
2006
IEEE
186views Hardware» more  ISCAS 2006»
14 years 1 months ago
Adaptive sliding mode control using simple adaptive control for SISO nonlinear systems
—Sliding mode control (SMC) has a strong capability of controlling nonlinear systems with uncertainties. However, it requires thorough knowledge of parameters and dynamics of the...
Muhammad Yasser, Agus Trisanto, Jianming Lu, Hiroo...
CDC
2010
IEEE
294views Control Systems» more  CDC 2010»
13 years 2 months ago
Adaptive self-triggered control over IEEE 802.15.4 networks
The communication protocol IEEE 802.15.4 is becoming pervasive for low power and low data rate wireless sensor networks (WSNs) applications, including control and automation. Never...
Ubaldo Tiberi, Carlo Fischione, Karl Henrik Johans...
ICDM
2009
IEEE
141views Data Mining» more  ICDM 2009»
13 years 5 months ago
Ensemble-Vis: A Framework for the Statistical Visualization of Ensemble Data
Scientists increasingly use ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using mu...
Kristin Potter, Andrew Wilson, Peer-Timo Bremer, D...
EH
2004
IEEE
105views Hardware» more  EH 2004»
13 years 11 months ago
Robust Sensor Systems using Evolvable Hardware
This paper describes a system that is robust with respect to sensor failure. The system utilizes multiple sensor inputs (three in this case) connected to a programmable device (FP...
James Hereford, Charles Pruitt
AROBOTS
2006
110views more  AROBOTS 2006»
13 years 7 months ago
Flying over the reality gap: From simulated to real indoor airships
Because of their ability to naturally float in the air, indoor airships (often called blimps) constitute an appealing platform for research in aerial robotics. However, when confr...
Jean-Christophe Zufferey, Alexis Guanella, Antoine...