Improving the Scalability of LoRa Networks Through Dynamical Parameter Set Selection

2019 ◽  
pp. 3-18
Author(s):  
Qingsong Cai ◽  
Jia Lin
Keyword(s):  
Dynamical Parameter

scholarly journals Novel Application of Fast Simulated Annealing Method in Brushless Motor Drive (BLMD) Dynamical Parameter Identification for Electric Vehicle Propulsion

2021 ◽  
Author(s):  
Richard A. Guinee
Keyword(s):  
Simulated Annealing ◽  
Parameter Identification ◽  
Electric Vehicle ◽  
Weight Ratio ◽  
Torque Control ◽  
Function Evaluation ◽  
Dynamical Parameter ◽  
Penalty Cost ◽  
Brushless Motor ◽  
Identification Strategy

Permanent magnet brushless motor drives (BLMD) are extensively used in electric vehicle (EV) propulsion systems because of their high power and torque to weight ratio, virtually maintenance free operation with precision control of torque, speed and position. An accurate dynamical parameter identification strategy is an essential feature in the adaptive control of such BLMD-EV systems where sensorless current feedback is employed for reliable torque control, with multi-modal penalty cost surfaces, in EV high performance tracking and target ranging. Application of the classical Powell Conjugate Direction optimization method is first discussed and its inaccuracy in dynamical parameter identification is illustrated for multimodal cost surfaces. This is used for comparison with the more accurate Fast Simulated Annealing/Diffusion (FSD) method, presented here, in terms of the returned parameter estimates. Details of the FSD development and application to the BLMD parameter estimation problem based on the minimum quantized parameter step sizes from noise considerations are provided. The accuracy of global parameter convergence estimates returned, cost function evaluation and the algorithm run time are presented. Validation of the FSD identification strategy is provided by excellent correlation of BLMD model simulation trace coherence with experimental test data at the optimal estimates and from cost surface simulation.

scholarly journals Comments on “Incorporating the Effects of Moisture into a Dynamical Parameter: Moist Vorticity and Moist Divergence”

2016 ◽  
Vol 31 (4) ◽  
pp. 1393-1396 ◽  
Author(s):  
David M. Schultz ◽  
Thomas Spengler
Keyword(s):  
Relative Humidity ◽  
Potential Vorticity ◽  
Single Case ◽  
Heavy Rain ◽  
Relative Vorticity ◽  
Dynamical Parameter ◽  
Accumulated Rainfall ◽  
Moist Potential Vorticity ◽  
Model Precipitation

Abstract In a recent article, Qian et al. introduced the quantities moist vorticity and moist divergence to diagnose locations of heavy rain. These quantities are constructed by multiplying the relative vorticity and divergence by relative humidity to the power k, where k = 10 in their article. Their approach is similar to that for the previously constructed quantity generalized moist potential vorticity. This comment critiques the approach of Qian et al., demonstrating that the moist vorticity, moist divergence, and by extension generalized moist potential vorticity are flawed mathematically and meteorologically. Raising relative humidity to the 10th power is poorly justified and is based on a single case study at a single time. No meteorological evidence is presented for why areas of moist vorticity and moist divergence should overlap with regions of 24-h accumulated rainfall. All three quantities have not been verified against the output of precipitation directly from the model nor is the approach of combining meteorological quantities into a single parameter appropriate in an ingredients-based forecasting approach. Researchers and forecasters are advised to plot the model precipitation directly and employ an ingredients-based approach, rather than rely on these flawed quantities.

Dynamical Parameter and State Estimation in Neuron Models

2011 ◽  
pp. 139-180 ◽  
Author(s):  
Henry D. I. Abarbanel ◽  
Paul H. Bryant ◽  
Philip E. Gill ◽  
Mark Kostuk ◽  
Justin Rofeh ◽  
...  
Keyword(s):  
State Estimation ◽  
Neuron Models ◽  
Dynamical Parameter

scholarly journals A Parameter Identification Method for Stewart Manipulator Based on Wavelet Transform

Mathematics ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 257
Author(s):  
Chenyang Zhang
Keyword(s):  
Wavelet Transform ◽  
Parameter Identification ◽  
Coulomb Friction ◽  
Velocity Analysis ◽  
Dynamical Parameter ◽  
New Approach ◽  
Identification Methods ◽  
Identification Method ◽  
True Value ◽  
Joint Velocity

Aiming at inertial and viscous parameter identification for the Stewart manipulator regardless of the influence of Coulomb friction, a simple and effective dynamical parameter identification method based on wavelet transform and joint velocity analysis is proposed in this paper. Compared with previously known identification methods, the advantages of the new approach are that (1) the excitation trajectory is easy to design, and (2) it can not only identify the inertial matrix, but also the viscous matrix accurately regardless of the influence of Coulomb friction. Comparison is made among the identification method proposed in this paper, another identification method proposed previously, and the true value calculated with a formula. The errors from results of different identification methods demonstrate that the method proposed in this paper shows great adaptability and accuracy.

A Synchronous Approach for Numerical Simulation of Machine Tools

2015 ◽  
Vol 642 ◽  
pp. 317-322
Author(s):  
Yunn Lin Hwang ◽  
Van Thuan Truong
Keyword(s):  
Numerical Simulation ◽  
Machine Tools ◽  
Flexible Structure ◽  
Dynamical Parameter ◽  
Resonance Frequencies ◽  
Body Dynamics ◽  
Computer Aided ◽  
Bode Diagram ◽  
Multi Body ◽  
And Control

In this paper, a synchronous approach for dynamic simulation of machine tools is described. Computer Aided Engineering (CAE) method models and analyzes a dynamical parameter prototype of machine tools. In which, the flexible structure, interactive movement, non-linear factor effects as well as characteristics of resonance frequencies and mechanical transfer function are considered. The integrating Finite Element Method (FEM), Multi-Body Dynamics (MBD) and control carries out a solution of machine tools simulation for predicting dynamic machine behaviors. The static analysis and modal analysis of components are presented with sample examples. Cybernetic characteristics like Bode diagram and such a controller are implemented for movement tailors. The synchronous approach deduces a practically technical method for machines tools.

Region-of-interest based dynamical parameter allocation for H.264/AVC encoder

2009 ◽  
Author(s):  
Minghui Wang ◽  
Tianruo Zhang ◽  
Chen Liu ◽  
Satoshi Goto
Keyword(s):  
Region Of Interest ◽  
Dynamical Parameter

scholarly journals Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks

2010 ◽  
Vol 4 (1) ◽  
pp. 69 ◽  
Author(s):  
Philipp Rumschinski ◽  
Steffen Borchers ◽  
Sandro Bosio ◽  
Robert Weismantel ◽  
Rolf Findeisen
Keyword(s):  
Parameter Estimation ◽  
Biochemical Reaction ◽  
Reaction Networks ◽  
Dynamical Parameter ◽  
Biochemical Reaction Networks ◽  
Model Invalidation

scholarly journals Dynamical parameter estimation using realistic photodetection

2004 ◽  
Vol 69 (4) ◽  
Author(s):  
P. Warszawski ◽  
Jay Gambetta ◽  
H. M. Wiseman
Keyword(s):  
Parameter Estimation ◽  
Dynamical Parameter

scholarly journals Dynamical parameter determinations in Pluto’s system

2012 ◽  
Vol 540 ◽  
pp. A65 ◽  
Author(s):  
L. Beauvalet ◽  
V. Lainey ◽  
J.-E. Arlot ◽  
R. P. Binzel
Keyword(s):  
Dynamical Parameter
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