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Related Experiment Video

Updated: Sep 16, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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Intelligent Robust Control Design with Closed-Loop Voltage Sensing for UPS Inverters in IoT Devices.

En-Chih Chang1, Yuan-Wei Tseng1, Chun-An Cheng1

  • 1Department of Electrical Engineering, I-Shou University, No. 1, Sec. 1, Syuecheng Rd., Dashu District, Kaohsiung City 84001, Taiwan.

Sensors (Basel, Switzerland)
|July 12, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an intelligent control technique for uninterruptible power supply (UPS) inverters in Internet of Things (IoT) devices. The method enhances performance and protects critical data from power outages.

Keywords:
IoT deviceUPS invertermodified gray fast variable structure sliding mode control (MGFVSSMC)neural network (NN)voltage sensing

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Area of Science:

  • Electrical Engineering
  • Control Systems
  • Artificial Intelligence

Background:

  • Uninterruptible Power Supply (UPS) inverters are crucial for protecting Internet of Things (IoT) devices and their data from power disruptions.
  • Existing control techniques for UPS inverters can suffer from prediction errors, leading to high harmonic distortion and degraded dynamic response, especially under challenging load conditions.

Purpose of the Study:

  • To propose an intelligent and robust control technique for UPS inverters in IoT applications.
  • To enhance the reliability and performance of UPS inverters by mitigating prediction errors and improving dynamic response.

Main Methods:

  • A modified gray fast variable structure sliding mode control (MGFVSSMC) is synthesized with a neural network (NN).
  • The MGFVSSMC ensures rapid system state convergence and eliminates chattering and steady-state errors.
  • The NN compensates for MGFVSSMC prediction errors caused by nonlinear loads or parameter variations.

Main Results:

  • The combined MGFVSSMC and NN control technique achieves fast transient response and low output voltage distortion.
  • The control strategy effectively compensates for prediction errors, maintaining high performance under diverse load conditions.
  • Simulations and digital signal processing (DSP) implementations validate the technique's effectiveness.

Conclusions:

  • The proposed intelligent control technique significantly improves UPS inverter performance for IoT devices.
  • The method offers robust protection against power outages and data loss.
  • The integration of MGFVSSMC with NN provides a reliable solution for high-performance UPS inverters.