Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal Journal of Robotics and Control (JRC) Journal of Fuzzy Systems and Control (JFSC)
Nguyen, Thanh-Trung
Unknown Affiliation
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Mechanical Engineering

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

Found 3 Documents
Search

 1 
ANFIS-based LQR Control for Rotary Double Parallel Inverted Pendulum Nguyen, Chi-Hung; Tran, Van-Si; Nguyen, Xuan-Hoang; Truong, Quang-Bao; Nguyen, Minh-Tuan; Luong, Nguyen-Phat; Ngo, Kha-Vy; Nguyen, Duc-Huy; Nguyen, Thanh-Trung; Le, Thi-Thanh-Hoang
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.v2i2.214

Abstract

This article explores two methodologies: Linear Quadratic Regulation (LQR) and the application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) on the Rotary Double Inverted Pendulum in Parallel Type (PRDIP) model. This model belongs to a class of underactuated robots, representing a nonlinear system with a mechanically simplistic configuration yet exhibiting considerable nonlinearity. Therefore, ANFIS is utilized to learn the input-output data, responses, and feedback of LQR. The response of the system's output to both LQR and ANFIS is compared to demonstrate the effectiveness of ANFIS in learning from the principles of LQR. This demonstration is supported through three cases: one simulation case and two experimental cases. Both control strategies are applied to the PRDIP system at the zero and -π positions, where one pendulum remains upright, and the other descends to counteract oscillations. The study presents simulation and experimental results to evaluate the points above comprehensively.
PID Control for Cart and Pole system: Simulation and Experiment Dang, Thai-Bao; Ngo, Truong-Doan-Hy; Tran, Thanh-Danh; Vo, Thi-Kieu-Tien; Lai, Nguyen-Ngoc-Truc; Huynh, Thi-My-Linh; Nguyen, Thi-My-Hang; Nguyen, Thi-My; Le, Tuong-Vy; Pham, Khanh-Hung; Huynh, Nguyen-Cuong; Nguyen, Anh-Tuan; Nguyen, Thanh-Trung
Journal of Fuzzy Systems and Control Vol. 2 No. 1 (2024): Vol. 2, No. 1, 2024
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v2i1.165

Abstract

Inverted pendulum (IP) is a single input-multi output (SIMO) nonlinear system that is popular in laboratories of control engineering. In this paper, we propose a structure of the PID control method – the most popular control method in the industry - for the cart and pole (C&P) system- a kind of IP. In this case, a suitable structure can help single input-single output (SISO) linear controllers to balance well. By this combination, the PID method can be used to stabilize this model at the equilibrium point. This controller is proven to work well in simulation. Therefore, we also present an experimental model which is created from the STM32F4 Discovery board for testing this algorithm. The experiment results again confirm the suitability of the method in simulation. Therefore, a survey of PID calibration is examined. The experimental survey confirms the suitability of this PID controller with theoretical points. The results from this study can be used to examine and train algorithms for learners in control laboratories.
Multiple Targets Path Planning for Document Delivering Mobile Robot in Dynamic Environments Vu, Van-Phong; Nguyen, Dinh-Hieu; Nguyen, Thanh-Trung; Tran, Minh-Duc
Journal of Robotics and Control (JRC) Vol. 6 No. 4 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i4.26660

Abstract

This paper proposes a method to control and make path planning for a delivering mobile robot that operates in a dynamic environment. The working environment is an office building that will appear both static obstacles and dynamic obstacles (such as such as people or other mobile robots). The mobile robot is designed to carry documents to multiple targets that are determined by users. Users can call the mobile robot and input the information of the documents and targets that need to be delivered via the website. The working environment map will be established by using LiDAR and SLAM technology. The path plaining is executed in two steps. Firstly, the ant colony algorithm (ACO) is employed to solve the indoor traveling salesman problem (ITSP), the TSP for indoor application, for determining the globally optimal moving schedule to multiple targets in this paper. Then, the shortest moving path between point to points for the delivering mobile robot is determined by using the Dijkstra algorithm. The shortest moving path for the delivering mobile robot is determined by using the Dijkstra algorithm. The ant colony algorithm (ACO) is employed to solve the inner traveling salesman problem (ITSP) to determine the optimal moving schedule to multiple targets in this paper. The dynamic window approach (DWA) methodology is applied to assist mobile robots in avoiding static and dynamic obstacles. In addition, the adaptive monte Carlo localization (AMCL) is used for positioning the mobile robot on the map. Finally, the simulation in MATLAB and Gazebo environment as well as the experiments, are presented to prove the superior success of the delivering mobile robot.
Co-Authors Dang, Thai-Bao Huynh, Nguyen-Cuong Huynh, Thi-My-Linh Lai, Nguyen-Ngoc-Truc Le, Thi-Thanh-Hoang Le, Tuong-Vy Luong, Nguyen-Phat Ngo, Kha-Vy Ngo, Truong-Doan-Hy Nguyen, Anh-Tuan Nguyen, Chi-Hung Nguyen, Dinh-Hieu Nguyen, Duc-Huy Nguyen, Minh-Tuan Nguyen, Thi-My Nguyen, Thi-My-Hang Nguyen, Xuan-Hoang Pham, Khanh-Hung Tran, Minh-Duc Tran, Thanh-Danh Tran, Van-Si Truong, Quang-Bao Vo, Thi-Kieu-Tien Vu, Van-Phong