Actively Controlling Anticipation of Irregular Events

1980 ◽  
Vol 32 (3) ◽  
pp. 435-446 ◽  
Author(s):  
Patrick Rabbitt ◽  
Subhash Vyas

There have been no investigations as to how people respond to sequences of events which occur at brief, unpredictable intervals as in everyday life. Eleven young adults were practised at a two-choice, continuous, serial choice-response task in which intervals between each response and the onset of the next signal (RSIs) varied randomly from trial to trial. On half the trials in each of four conditions the RSI was 20 ms, and on the other trials 200, 400, 800 and 1600 ms respectively. Reaction times fell as RSIs increased from 20-200 ms but thereafter appeared to be unaffected by RSI duration. In the 20/200 and 20/400 ms RSI conditions RT was not affected by transitions between different RSIs but in the 20/800 and 20/1600 ms conditions RTs were faster when the longer RSI recurred on immediately successive trials than if the long RSI followed the short (20 ms) RSI. These results are discussed in terms of a control system model for the way in which subjects actively trade off between their internal performance limitations to optimally meet task demands.

2014 ◽  
Vol 548-549 ◽  
pp. 819-823
Author(s):  
Xi Juan Wang ◽  
Tao Zhou ◽  
Jing Xiao Feng ◽  
Yu Peng Pei

In the AC control system, vector control theory is very popular as it makes the AC motor achieve the performance as perfect as DC motor [1]. In the paper, the vector control theory is briefly introduced, and then a vector control system model is builded in the matlab/simulink, and the SVPWM technique is adopted. The results show that the improved vector control sytem of PMSM has a excellent performance.


2020 ◽  
Vol 154 ◽  
pp. 02009
Author(s):  
Stanisław Lis ◽  
Marcin Tomasik ◽  
Sławomir Kurpaska ◽  
Jarosław Knaga ◽  
Piotr Łyszczarz

The article presents the analysis of the automatic control of the bioethanol production process intended for biofuel. It presents the formulated general concept of the system and the method of designing a closed control system based on the iterative prototyping procedure. The modeling and the simulation were carried out in the Matlab®-Simulink environment. The simulation model of the object was developed based on the experimentally registered characteristics. It has been adjusted, i.e. the compatibility of its behavior with the object it reproduces has been confirmed. Based on the tuned model of the object, a control system model was created, which was the basis for computer simulation which enabled the control algorithm parameters to be established. The final verification of the correct operation of the system was performed with the use of hardware simulation. It was based on entering a negative feedback loop of the virtual control system of the real object elements into the loop. The results of the simulation confirmed the correctness of the adopted design.


2012 ◽  
Vol 190-191 ◽  
pp. 987-992 ◽  
Author(s):  
Ying Pu Cui ◽  
Long Hua She ◽  
Xiao Long Li ◽  
A Ming Hao

Firstly, build the suspension-control-system model under the condition of elastic guideway, and design the controller. Secondly, design the Kalman forecaster based on model, and diagnose the fault by comparing forecasted value with real value. Finally, verify the effectiveness of this fault diagnosis method for suspension signal by simulation.


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