A Novel Integrated Control Strategy for a Cost-effective Inverted Pendulum System with Camera-based Observation
Received: 14 February 2025 | Revised: 10 March 2025 | Accepted: 19 March 2025 | Online: 28 March 2024
Corresponding author: Ngoc-Khoat Nguyen
Abstract
To improve the ability to control the balance of an inverted pendulum on a cart system, a refined fuzzy logic inference approach using the Sugeno model is introduced. This new approach leverages the capabilities of the ESP32 CAM and YOLO v3. The ESP32 CAM provides real-time image and video capture, whereas YOLO v3, operating on a more robust processing platform, performs object detection within the captured data. This integration of image processing and object recognition necessitates a complex experimental setup, requiring further refinement of the adaptable robotic model and integration of various techniques. A WinForms interface has been developed for the control and monitoring of the camera-equipped inverted pendulum system. This interface allows the users to monitor and adjust the system parameters, as well as to visualize the surrounding environment. This design significantly enhances the sophistication of the control and monitoring system while maintaining cost-effectiveness. Numerical simulations and experimental results demonstrate markedly improved control performance, validating the novel integrated control methodology.
Keywords:
inverted pendulum system, observation, image processing, YOLOv3, integrated control methodologyDownloads
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Copyright (c) 2025 Ngoc-Khoat Nguyen, Thi-Mai-Phuong Dao, Van-Hung Pham, Tien-Dung Nguyen, Thi-Kim-Thanh Tran, Van-Tien Nguyen
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