Vo-Hoang-Lap Tran 1, Duc-Anh-Quan Nguyen 1, Hoang-Dung Nguyen 1, Anh-Khoa Dang 1, The-Hoang Pham 1, Thai-Hieu-Phong Tran 1, Gia-Bao Nguyen 1, Minh-Phuoc Cu 2*
1 Ho Chi Minh City University of Technology and Education (HCMUTE)
Vo Van Ngan Street, Ho Chi Minh City, Vietnam
2 Cao Thang Technical College
65 Huynh Thuc Khang Street, Ben Nghe Ward, District 1, Ho Chi Minh City
* Corresponding author. Email: cuminhphuoc@caothang.edu.vn
Robotica & Management, Vol. 29, No. 2, pp. 49-56
DOI: https://doi.org/10.24193/rm.2024.2.7
Abstract: Throughout the evolution of automatic control, numerous controllers have been developed with the primary goal of stabilizing systems through proven algorithms. One of the most crucial tasks in controller design is optimizing the controller itself. In this paper, our team presents an evolutionary algorithm known as Particle Swarm Optimization (PSO), inspired by the social behavior and cognitive processes of organisms such as fish schools and bird flocks. With the Backstepping controller successfully designed for our ball and beam system, we will use the PSO algorithm to fine-tune the controller’s parameters for optimal performance. The ultimate objective is to stabilize the ball and beam system, meaning the ball must remain steady at the desired position. Our team will conduct multiple trials, gathering data from the PSO algorithm, which will allow us to compare the control quality of the solutions we find. The system will be tested both in simulations and in practical experiments to verify its accuracy.
Keywords: Ball and Beam system, Particle Swarm Optimization, PSO, Backstepping controller.
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