Design of SCR Control Software Based on Dual-Core Processor

2013 ◽  
Vol 457-458 ◽  
pp. 1130-1133
Author(s):  
Jie Hui Li ◽  
Qing Yu ◽  
Lu Yun Zhang ◽  
Tie Nan Huang

This paper introduces the control software of SCR system based on the dual-core processor S12XEP100. By the reasonable coordination between the host processor and the coprocessor XGATE, the SCR control system satisfies the increasing demands for real-time. Control performance tests show that the control software of SCR system meets the basic control requirements, also improves the real-time performance of programs effectively, such as urea injection frequency, urea injection quantity and the stability of common rail pipe pressure.

2013 ◽  
Vol 850-851 ◽  
pp. 553-556
Author(s):  
Qun Yong Ou

An inverted pendulum is a classic control problem and is widely used as a benchmark for testing various control algorithms. First, this paper analyse the dynamic and non-linear model of the inverted pendulum, then focus on the real-time control of the inverted pendulum, we developed real-time control software for the single-stage inverted pendulum by using Visual C++ 2010, its mainly operate API functions to control board and implement various control algorithms.


2021 ◽  
Author(s):  
Zhufeng Lu

<div><p>In this work, an EEG-based control paradigm assisted by micro-facial-expressions (microFE-BCI) was developed, focusing on the mainstream defect as the insufficiency of real-time capability, asynchronous logic, and robustness. The core algorithm in microFE-BCI contained two stages (asynchronous ‘ON’ detection & microFE-BCI based real-time control) with four steps (obvious non-microFE-EEGs exclusion, interface ‘ON’ detection, microFE-EEGs real-time decoding, and validity judgment). It provided the asynchrounous function, decoded 8 instructions from the latest 100 ms EEGs, and greatly reduced the frequent misoperation. In the offline assessment, microFE-BCI achieved 96.46%±1.07 accuracy for interface ‘ON' detection and 92.68%±1.21 for microFE-EEGs real-time decoding, with the theoretical output timespan less than 200 ms. This microFE-BCI was implemented into a software, and applied to two online manipulations for evaluating the stability and agility. In object-moving with a robotic arm, the averaged IoU was 60.03±11.53%. In water-pouring with a prosthetic Hand, the averaged water volume was 202.5±7.0 ml. During online, microFE-BCI performed no significant difference (P = 0.6521 & P = 0.7931) with commercial control methods (i.e., FlexPendant and Joystick), indicating a similar level of controllability and agility. This study demonstrated the capability of microFE-BCI, enabling a novel solution to the noninvasive BCIs in real-world challenges.</p></div>


Author(s):  
Carlos Colodro-Conde ◽  
Luis F. Rodríguez-Ramos ◽  
Isidro Villó ◽  
Craig Mackay ◽  
Rafael Rebolo ◽  
...  

2004 ◽  
Vol 71 (1-4) ◽  
pp. 65-69 ◽  
Author(s):  
D Mastrovito ◽  
J Ferron ◽  
D Gates ◽  
T Gibney ◽  
R Johnson

Sign in / Sign up

Export Citation Format

Share Document