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All Journal Journal of Fuzzy Systems and Control (JFSC) Control Systems and Optimization Letters Scientific Journal of Engineering Research
Phung, Son-Thanh
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Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Journal : Control Systems and Optimization Letters

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Trajectory Tracking Controller Design for a One-degree-of-Freedom Robotic Arm using Fuzzy Logic and Neural Controllers Nguyen, Quang-Thien; Nguyen, Anh-Huy; Le, Hoang-Linh; Nguyen, Hai-Thanh; Le, Thi-Hong-Lam; Nguyen, Ngoc-Hung; Nguyen, Van-Hiep; Nguyen, Thanh-Binh; Nguyen, Thi-Ngoc-Thao; Nguyen, Minh-Tam; Nguyen, Phong-Luu; Le, Hoang-Lam; Phung, Son-Thanh
Control Systems and Optimization Letters Vol 4, No 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v4i1.271

Abstract

The one-degree-of-freedom (1-DOF) robotic arm is a fundamental platform widely used in laboratories for teaching and evaluating position and trajectory control strategies. This paper presents the modeling, simulation, and experimental implementation of a 1-DOF robotic arm system using intelligent control approaches. A Fuzzy Logic Controller (FLC) and a neural network controller (NNC) based on a multi-layer perceptron (MLP) were designed and evaluated in MATLAB/Simulink and implemented in real time on an STM32F4 embedded hardware platform. Both controllers were tested under step and sinusoidal reference inputs, achieving tracking errors below 5°, settling times of approximately 0.1 s (within ±2%), and limited overshoot. Although the neural network successfully reproduced the general control behavior of the FLC, the fuzzy controller demonstrated slightly smoother responses and lower control effort under multi-level step conditions. A primary contribution of this work is the development and validation of a low-cost STM32F4G-based embedded platform for implementing and experimentally evaluating intelligent control algorithms, providing a practical and scalable solution for intelligent control research and laboratory education in universities.
Co-Authors Huynh, Thanh-Tuan Le, Hoang-Lam Le, Hoang-Linh Le, Thi-Hong-Lam Nghia, Bui-Duc Nguyen, Anh-Huy Nguyen, Binh-Hau Nguyen, Hai-Thanh Nguyen, Hoang-Thong Nguyen, Huy-Bao Nguyen, Le-Minh-Kha Nguyen, Minh-Tam Nguyen, Ngoc-Hung Nguyen, Phong-Luu Nguyen, Quang-Khai Nguyen, Quang-Thien Nguyen, Quoc-Thuan Nguyen, Thanh-Binh Nguyen, Thanh-Toan Nguyen, Thi-Ngoc-Thao Nguyen, Van-Dong-Hai Nguyen, Van-Hiep Nguyen, Van-Tuan Phan, Anh-Quoc Tran, Huy-Vu Tran, Phuoc-Dat Vo, Kim-Thanh