Comparison of Several Nonlinear Filters for a Benchmark Tracking Problem

2006 ◽  
Author(s):  
Christopher Karlgaard ◽  
Hanspeter Schaub
Keyword(s):  
Nonlinear Filters ◽  
Tracking Problem

Removal of Mixed Poisson and Impulse Noise in 1-D Signals by Non-Adaptive and Adaptive Nonlinear Filters

2008 ◽  
Vol 67 (14) ◽  
pp. 1247-1267
Author(s):  
V. V. Lukin ◽  
S. Peltonen ◽  
P. Ye. Yeltsov ◽  
S. K. Abramov ◽  
A. N. Besedin ◽  
...  
Keyword(s):  
Impulse Noise ◽  
Nonlinear Filters

Neural Torque Controllers For Trajectory Tracking Problem Of A Nonholonomic Mobile Robot

2007 ◽  
Vol 5 (2) ◽  
pp. 121-136
Author(s):  
N. Martins ◽  
D. Bertol ◽  
W. Lombardi ◽  
E. R. Pieri ◽  
E. Castelan
Keyword(s):  
Mobile Robot ◽  
Trajectory Tracking ◽  
Tracking Problem ◽  
Nonholonomic Mobile Robot

scholarly journals Stability of the Tracking Problem with Task-Priority Inverse Kinematics

2018 ◽  
Vol 51 (22) ◽  
pp. 121-125 ◽  
Author(s):  
Mathias Hauan Arbo ◽  
Jan Tommy Gravdahl
Keyword(s):  
Inverse Kinematics ◽  
Tracking Problem ◽  
Task Priority

scholarly journals Online Learning Algorithms for the Real-Time Set-Point Tracking Problem

2021 ◽  
Vol 11 (14) ◽  
pp. 6620
Author(s):  
Arman Alahyari ◽  
David Pozo ◽  
Meisam Farrokhifar
Keyword(s):  
Decision Making ◽  
Power Systems ◽  
Real Time ◽  
Demand Response ◽  
Tracking Problem ◽  
Smart Meters ◽  
Set Point ◽  
Point Tracking ◽  
Power Set ◽  
Decision Making Framework

With the recent advent of technology within the smart grid, many conventional concepts of power systems have undergone drastic changes. Owing to technological developments, even small customers can monitor their energy consumption and schedule household applications with the utilization of smart meters and mobile devices. In this paper, we address the power set-point tracking problem for an aggregator that participates in a real-time ancillary program. Fast communication of data and control signal is possible, and the end-user side can exploit the provided signals through demand response programs benefiting both customers and the power grid. However, the existing optimization approaches rely on heavy computation and future parameter predictions, making them ineffective regarding real-time decision-making. As an alternative to the fixed control rules and offline optimization models, we propose the use of an online optimization decision-making framework for the power set-point tracking problem. For the introduced decision-making framework, two types of online algorithms are investigated with and without projections. The former is based on the standard online gradient descent (OGD) algorithm, while the latter is based on the Online Frank–Wolfe (OFW) algorithm. The results demonstrated that both algorithms could achieve sub-linear regret where the OGD approach reached approximately 2.4-times lower average losses. However, the OFW-based demand response algorithm performed up to twenty-nine percent faster when the number of loads increased for each round of optimization.

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