A Simple Virtual Sensor for Combustion Timing

2003 ◽  
Vol 125 (3) ◽  
pp. 462-467 ◽  
Author(s):  
U. Holmberg ◽  
M. Hellring
Keyword(s):  
Closed Loop ◽  
Low Complexity ◽  
Peak Position ◽  
Ion Current ◽  
Virtual Sensor ◽  
Loop Control ◽  
Spark Plug ◽  
Crank Angle ◽  
Pressure Peak ◽  
Order Of Magnitude

A low-complexity virtual sensor for the pressure peak position of the crank angle in a spark-ignited car motor is proposed. The algorithm estimates the pressure peak position from the ion current, measured from the spark plug. The complexity of the algorithm is an order of magnitude smaller than any other proposed schemes. Still, performance is not sacrificed. Closed-loop control is demonstrated on a SAAB 9000 driven on the highway.

A Sub 0.8 Degree per Hour Mode-Matching MEMS Vibratory Gyroscope with Closed Loop Control for the Sense Mode

2013 ◽  
Vol 562-565 ◽  
pp. 260-264
Author(s):  
Chun Hua He ◽  
Qian Cheng Zhao ◽  
Da Chuan Liu ◽  
Zhen Chuan Yang ◽  
Gui Zhen Yan
Keyword(s):  
Closed Loop ◽  
Open Loop ◽  
Closed Loop Control ◽  
Mode Matching ◽  
Sense Mode ◽  
Loop Control ◽  
Vibratory Gyroscope ◽  
Closed Loop Control System ◽  
Loop Control System ◽  
Order Of Magnitude

A detailed analysis about the nonlinearity of a mode-matching MEMS vibratory gyroscope is presented in this paper, then closed loop control for the sense mode is adopted to improved the performances. Experimental results figure out that the mode-matching gyroscope with closed loop controlled sense mode achieves a scale factor of 65mV/deg/s with nonlinearity of 0.05% and asymmetry of 0.1%, and a bias instability of 0.77deg/h, while they are 60mV/deg/s, 1%, 4.6% and 9.8deg/h in the open loop controlled sense mode system, respectively. These performances can be improved by more than one order of magnitude in the closed loop control system.

The Impact of Visual Feedback Type on the Mastery of Visuo-Motor Transformations

2012 ◽  
Vol 220 (1) ◽  
pp. 3-9 ◽  
Author(s):  
Sandra Sülzenbrück
Keyword(s):  
Empirical Research ◽  
Visual Feedback ◽  
Closed Loop ◽  
Motor Planning ◽  
Visual Input ◽  
Closed Loop Control ◽  
Loop Control ◽  
Feedback Type ◽  
Effective Use ◽  
The Impact

For the effective use of modern tools, the inherent visuo-motor transformation needs to be mastered. The successful adjustment to and learning of these transformations crucially depends on practice conditions, particularly on the type of visual feedback during practice. Here, a review about empirical research exploring the influence of continuous and terminal visual feedback during practice on the mastery of visuo-motor transformations is provided. Two studies investigating the impact of the type of visual feedback on either direction-dependent visuo-motor gains or the complex visuo-motor transformation of a virtual two-sided lever are presented in more detail. The findings of these studies indicate that the continuous availability of visual feedback supports performance when closed-loop control is possible, but impairs performance when visual input is no longer available. Different approaches to explain these performance differences due to the type of visual feedback during practice are considered. For example, these differences could reflect a process of re-optimization of motor planning in a novel environment or represent effects of the specificity of practice. Furthermore, differences in the allocation of attention during movements with terminal and continuous visual feedback could account for the observed differences.

118-LB: Glucose Variability throughout the Menstrual Cycle on Closed-Loop Control in Type 1 DM

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 118-LB
Author(s):  
CAROL J. LEVY ◽  
GRENYE OMALLEY ◽  
SUE A. BROWN ◽  
DAN RAGHINARU ◽  
YOGISH C. KUDVA ◽  
...  
Keyword(s):  
Menstrual Cycle ◽  
Closed Loop ◽  
Glucose Variability ◽  
Closed Loop Control ◽  
Loop Control ◽  
Type 1 Dm

101-LB: Eighteen-Month Use of Closed-Loop Control (CLC): A Randomized, Controlled Trial

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 101-LB
Author(s):  
SUE A. BROWN ◽  
DAN RAGHINARU ◽  
BRUCE A. BUCKINGHAM ◽  
YOGISH C. KUDVA ◽  
LORI M. LAFFEL ◽  
...  
Keyword(s):  
Randomized Controlled Trial ◽  
Closed Loop ◽  
Controlled Trial ◽  
Closed Loop Control ◽  
Loop Control ◽  
Randomized Controlled
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