Non-Linear Modelling and Simulation of a 4/2 Pole Switch Reluctance Motor

2016 ◽  
Author(s):  
Guest Editor Jianping Du
Keyword(s):  
Modelling And Simulation ◽  
Switch Reluctance Motor ◽  
Reluctance Motor ◽  
Linear Modelling ◽  
Non Linear

Non-linear modelling and optimal control of a hydraulically actuated seismic isolator test rig

2013 ◽  
Vol 35 (1-2) ◽  
pp. 255-278 ◽  
Author(s):  
Stefano Pagano ◽  
Riccardo Russo ◽  
Salvatore Strano ◽  
Mario Terzo
Keyword(s):  
Optimal Control ◽  
Test Rig ◽  
Seismic Isolator ◽  
Linear Modelling ◽  
Non Linear ◽  
Hydraulically Actuated

Mixed-effect non-linear modelling for diameter estimation along the stem of Tectona grandis in mid-western Brazil

2018 ◽  
Vol 81 (2) ◽  
pp. 167-173 ◽  
Author(s):  
Luciano Rodrigo Lanssanova ◽  
Sebastião do Amaral Machado ◽  
Alexandre Techy de Almeida Garrett ◽  
Izabel Passos Bonete ◽  
Allan Libanio Pelissari ◽  
...  
Keyword(s):  
Tectona Grandis ◽  
Mixed Effect ◽  
Linear Modelling ◽  
Non Linear

scholarly journals Applications of a working framework for the measurement of representative learning design in Australian football

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242336
Author(s):  
Peter R. Browne ◽  
Carl T. Woods ◽  
Alice J. Sweeting ◽  
Sam Robertson
Keyword(s):  
Association Rule ◽  
Analytical Techniques ◽  
Competitive Environment ◽  
Skill Transfer ◽  
Learning Design ◽  
Training Task ◽  
Linear Modelling ◽  
Non Linear ◽  
Australian Football ◽  
Insight Into

Representative learning design proposes that a training task should represent informational constraints present within a competitive environment. To assess the level of representativeness of a training task, the frequency and interaction of constraints should be measured. This study compared constraint interactions and their frequencies in training (match simulations and small sided games) with competition environments in elite Australian football. The extent to which constraints influenced kick and handball effectiveness between competition matches, match simulations and small sided games was determined. The constraints of pressure and time in possession were assessed, alongside disposal effectiveness, through an association rule algorithm. These rules were then expanded to determine whether a disposal was influenced by the preceding disposal. Disposal type differed between training and competition environments, with match simulations yielding greater representativeness compared to small sided games. The subsequent disposal was generally more effective in small sided games compared to the match simulations and competition matches. These findings offer insight into the measurement of representative learning designs through the non-linear modelling of constraint interactions. The analytical techniques utilised may assist other practitioners with the design and monitoring of training tasks intended to facilitate skill transfer from preparation to competition.

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