Claim Missing Document
Check
Articles

Found 5 Documents
Search

PID Control for Balancing Bike Model using Reaction Wheel Tran, Thi-Ngoc-Tram; Ho, Thanh-Viet; Nguyen, Huu-Loi; Le, Ngoc-Nam; Tran, Van-Phuc; Tran, Quoc-Bao; Mai, Pham-Phuong; Pham, Ngoc-Duy; Bui, Tien-Phat; Le, Thi-Hong-Lam
Journal of Fuzzy Systems and Control Vol. 2 No. 2 (2024): Vol. 2, No. 2, 2024
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v2i2.188

Abstract

Motorcycles or bicycles are known as unbalanced systems like the inverted pendulum model. Normally, we must use a handlebar to control the Motorcycles or bicycles. In this paper, the authors propose a PID controller for a balance bike using a reaction wheel. The authors formulated a mathematical model for the system and performed simulation testing using MATLAB to control it. Also, the simulation model of the balance bike system using a reaction wheel has been developed to assess the feasibility of building and controlling the system without relying on its mathematical model. The study will explicitly provide the performance of the PID algorithm in controlling a balanced bike using a reaction wheel.
Experiment Ball Levitation with Fuzzy PID and PID Implementation Nguyen, Hoang-Thuat; Dao, Anh-Quan; Hoang, Van-Phu-Quy; Nguyen, Quyen-Anh; Dang, Truong-Phu; Tang, Minh-Nam; Le, Vu-Huy; Bui, The-Nam-Vuong; Nguyen, Tien-Dung; Le, Thi-Hong-Lam
Journal of Fuzzy Systems and Control Vol. 2 No. 3 (2024): Vol. 2, No. 3, 2024
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v2i3.221

Abstract

The “Ball Levitation” experiment can be easily recognized, like iFly in Singapore, and is greatly integrated into industrial fields such as flow control systems, aerodynamic testing, the oil and gas industry, HVAC systems, etc. Therefore, it is utilized in university laboratories for student exploration of non-linear control technology. The main objective of this experiment is through the position of the ball which is measured by an ultrasonic sensor to execute the PWM of the blower fan in order to control the speed of one so that the ball can be stabilized consistently at a specific height. Despite its uncomplicated model, the challenge of this model is from non-linear effects on the ball and the intricate physics governing its movement. Moreover, the ball is highly responsive to external influences from the blower fan. Consequently, conventional mathematical control methods struggle to handle it, making the simulation and comparison of control algorithms challenging. A Fuzzy-PID controller is meticulously designed to automatically stabilize the ball's position by considering the PID parameters with pre-defined fuzzy rules due to the actual showcase of the model. This setup allows us to experimentally compare the traditional PID controller with the Fuzzy-PID controller. The results reveal notable differences in the performance characteristics of these controllers.
Experimental Swing-Up Control of Advanced Sliding and Energy-based Modes for Pendubot Tran, Minh-Duy; Trinh, Minh-Phu; Do, Nguyen-Son; Phan, Thai-Chan; Ngo, Tan-Bao-Chau; Nguyen, Viet-Thuan; Ngo, Viet-Dung; Hoang, Ngoc-Quan; Trinh, Tan-Phong; Le, Thi-Hong-Lam
Journal of Fuzzy Systems and Control Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i1.277

Abstract

This study focuses on the implementation and comparative evaluation of two swing-up control strategies—Energy-Based Methods (EBM) and Advanced Sliding Mode Control (ASMC)—for pendubot, a nonlinear two-link robotic system. While previous research has extensively explored balancing algorithms for this model, swing-up strategies have primarily been analyzed through simulations, with limited application to real-world systems. This research addresses this gap by deploying both EBM and ASMC on a physical pendubot model. Practical results are presented to provide the most accurate evaluation of the control quality of each algorithm.
PID-CONTROLLED HUMAN DETECTION ROBOT WITH VISUAL PROCESSING ON ALPHABOT-2 Nguyen, Hoang-Thong; Vo, Quoc-Thang; Le, Minh-Thiet; Truong, Cong-Tuan; Tran, Duy-Dat; Pham, Cong-Hoang-Anh; Cao, Huu-Tai; Lam, Gia-Bao; Truong, Hoang-Anh; Tran, Le-Bao-Luan; Nguyen, Hoang-Quang-Minh; Nguyen, Le-Hoang-Viet; Le, Thi-Hong-Lam
Indonesian Journal of Engineering and Science Vol. 6 No. 2 (2025): Table of Contents
Publisher : Asosiasi Peneliti Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51630/ijes.v6i2.176

Abstract

This paper presents a human detection and alert robot system based on the AlphaBot2 platform and Raspberry Pi. The system employs a camera with a HOG-based human detection algorithm to locate the target within the frame and uses an ultrasonic sensor to measure the distance to the person. Based on the horizontal offset between the person and the frame centre, the PID controller adjusts the speeds of two DC motors to guide the robot smoothly and steadily toward the person. When the robot reaches a predefined distance from the detected human target, a buzzer is triggered. Through experiments, the effectiveness of the image processing and PID algorithm is evaluated, and optimal parameter values are identified for the system.
DESIGN OF A FUZZY CONTROLLER FOR A HEATING FURNACE SYSTEM To, Nguyen-Nhut-Huy; Pham, Quoc-Huy; Le, Anh-Quoc; Doan, Minh-Tu; Pham, Minh-Tri; Tran, Ngoc-Huy; Nguyen, Hoang-Thien-Phuc; Tran, Thanh-Tu; Phan, Minh-Nhat; Nguyen, Phuc-Loc; Dao, Duy-Anh; Nguyen, Thai-Bao; Le, Thi-Hong-Lam
Indonesian Journal of Engineering and Science Vol. 6 No. 2 (2025): Table of Contents
Publisher : Asosiasi Peneliti Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51630/ijes.v6i2.182

Abstract

In thermal process control, conventional methods like PID often struggle to cope with nonlinearities, time delays, and external disturbances. This study presents the design and implementation of a Mamdani-type fuzzy logic controller for temperature regulation in furnace systems. Unlike traditional controllers, fuzzy logic offers flexibility, robustness, and does not require an accurate mathematical model. The proposed controller uses two input variables—temperature error and its rate of change—and one output variable to adjust the TRIAC firing angle, controlling the system's power input. Through MATLAB simulation and hardware implementation with LM35 sensors and TRIAC modules, the fuzzy system demonstrates rapid response, no overshoot, and stable operation across varying setpoints (50°C, 70°C, 90°C). Comparative results highlight the superior performance of fuzzy control over conventional PID, especially in systems with nonlinear behavior and dynamic characteristics. The findings confirm that fuzzy logic is a practical and efficient solution for real-time temperature control applications, offering high adaptability without manual parameter tuning.