Article Per Year (5 Year)
p-Index From 2021 - 2026
0.562
P-Index
This Author published in this journals
All Journal Journal of Fuzzy Systems and Control (JFSC) Control Systems and Optimization Letters
Phong-Luu Nguyen
Ho Chi Minh City University of Technology and Engineering (HCM-UTE)
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Design and Implementation of PID and Fuzzy-PID Controllers for Ball-on-Plate Quoc-Khanh Tran; Pham-Minh-Trong Vo; Hoang-Dung Nguyen; Tran-Nhat Dang; Thi-Ngoc-Thao Nguyen; Thi-Hong-Lam Le; Phong-Luu Nguyen; Thanh-Binh Nguyen; Van-Hiep Nguyen; Ngoc-Long Le
Journal of Fuzzy Systems and Control Vol. 4 No. 2 (2026): Vol. 4 No. 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i2.380

Abstract

This paper presents the design, implementation, and comparative evaluation of a conventional PID controller and a Fuzzy-PID controller for a nonlinear Ball-on-Plate (BoP). The primary objective is to stabilize the ball at a desired position on the plate while achieving a fast transient response and robustness against disturbances. A conventional PID controller is first designed and tuned using the Ziegler–Nichols method. To improve performance under nonlinear conditions, a Fuzzy-PID controller is developed in which fuzzy logic adaptively adjusts the PID gains online. The proposed controllers are evaluated through three stages: numerical simulation in MATLAB/Simulink, real-time implementation in Python, and experimental validation on a physical hardware platform. Compared with the conventional PID controller, the Fuzzy-PID controller achieves a reduction in maximum overshoot from 0.17% to below 0.1% in simulation, a shorter settling time (approximately 4.0 s for PID versus 2.8 s for Fuzzy-PID), and a reduction in steady-state positioning error of approximately 33–36% in hardware experiments (from ~3–14 pixels to ~2–9 pixels).
Comparative Evaluation of Fuzzy Logic, Sliding Mode, and LQR Controllers for DC Motor Position Control Minh-Thy Pham; Lam-Trong-Tuan Bui; Thi-Thanh-Hoang Le; Van-Bac Nguyen; Le-Khoi-Nguyen Cao; Le-Nhat-Minh Tran; Xuan-Manh Ngo; Phong-Luu Nguyen; Dinh-Phu Nguyen
Journal of Fuzzy Systems and Control Vol. 4 No. 2 (2026): Vol. 4 No. 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i2.405

Abstract

This paper presents a comparative evaluation of three advanced control strategies for DC motor position control, namely Fuzzy Logic Control (FLC), Sliding Mode Control (SMC), and Linear Quadratic Regulator (LQR). First, the mathematical model of the DC motor is derived from the electrical and mechanical dynamic equations. Based on this model, the three controllers are designed and implemented in MATLAB/Simulink and experimentally validated on a microcontroller-based platform under identical operating conditions. The comparative analysis is performed using quantitative performance indices, including settling time, overshoot, steady-state error, and control effort. Simulation and experimental results show that the SMC controller provides the best overall performance with fast convergence, high robustness, and small steady-state error, while the FLC approach achieves smoother responses with moderate transient performance. The LQR controller demonstrates rapid state regulation but produces larger transient peaks and higher control effort compared with the other methods. The results highlight the practical trade-offs among intelligent, robust, and optimal control strategies for low-cost DC motor position control applications.
Trajectory Tracking Controller Design for a One-degree-of-Freedom Robotic Arm using Fuzzy Logic and Neural Controllers Quang-Thien Nguyen; Anh-Huy Nguyen; Hoang-Linh Le; Hai-Thanh Nguyen; Thi-Hong-Lam Le; Ngoc-Hung Nguyen; Van-Hiep Nguyen; Thanh-Binh Nguyen; Thi-Ngoc-Thao Nguyen; Minh-Tam Nguyen; Phong-Luu Nguyen; Hoang-Lam Le; Son-Thanh Phung
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 Anh-Huy Nguyen Dinh-Phu Nguyen Hai-Thanh Nguyen Hoang-Dung Nguyen Hoang-Lam Le Hoang-Linh Le Lam-Trong-Tuan Bui Le-Khoi-Nguyen Cao Le-Nhat-Minh Tran Minh-Tam Nguyen Minh-Thy Pham Ngoc-Hung Nguyen Ngoc-Long Le Pham-Minh-Trong Vo Quang-Thien Nguyen Quoc-Khanh Tran Son-Thanh Phung Thanh-Binh Nguyen Thi-Hong-Lam Le Thi-Ngoc-Thao Nguyen Thi-Thanh-Hoang Le Tran-Nhat Dang Van-Bac Nguyen Van-Hiep Nguyen Xuan-Manh Ngo