.png){kind=icon}
.png){kind=icon}
Return
Optimization method for single-chip microcontroller control system based on IPSO algorithm and back-propagation algorithm
.png){kind=icon}
PRE
AI
DOI：10.1088/2631-8695/ae546d.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
With the development of technology, single-chip microcontroller control systems have been widely used. However, they also face challenges such as long processing time, error accumulation, and susceptibility to interference. To address these issues, the study introduces back-propagation algorithm to optimize particle swarm optimization algorithm, and introduces proportional-integral-derivative controller, ultimately constructing a single-chip microcontroller control system. The data accuracy of optimized single-chip microcontroller control systems is evaluated using different models under different temperature conditions. At -80 degrees C, -40 degrees C, 0 degrees C, 40 degrees C, and 80 degrees C, the accuracy of the single-chip microcontroller control system was 92.04%, 93.56%, 97.16%, 95.09%, and 94.20%, respectively. The power consumption of different single-chip microcontroller control systems was compared. The current and voltage curves of the particle swarm optimization-back-propagation and back-propagation single-chip microcontroller control systems were higher than those of the proposed single-chip microcontroller control system, with a minimum difference of 0.3mV and a maximum difference of 1.2mV. The proposed single-chip microcontroller control system has lower energy consumption, higher accuracy, stronger stability, and anti-interference capability.
Keywords:
particle swarm optimization
back-propagation
single-chip microcontroller
differential evolution algorithm
PID controller
Journal
E
IF:
1.6
Papers:
2.1K
Citations:
0