Analysis of Linear and Intelligent Control for Balancing Pendubot System - Tran, Minh-Duy; Le, Diep-Thuy-Duong; Phan, Hong-Phuoc; Vo, Hoang-Viet; Ngo, Dang-Quang-Tinh; Nguyen, Ngoc-Duy; Nguyen, Tan-Phat; Tran, Nhat-Linh; Vo, Thanh-An; Le, Thi-Thanh-Hoang (Journal of Fuzzy Systems and Control, 2025)
Pendubot is a typical under-actuated SIMO control system, commonly used in research on control algorithms. Rather than focusing on analyzing a single control algorithm, this paper provides an overview of control efficiency as well as differences between algorithms through analytical assessments. In this study, the authors analyzed algorithms including feedback linearization (a linear algorithm), LQR – optimal control (a linear algorithm), and fuzzy control (an intelligent algorithm) to stabilize the model at the equilibrium position of the TOP position – where both bars of the system stand upright in the opposite direction to gravity. The genetic algorithm (GA) is used to optimize control parameters for the model. These algorithms are simulated in MATLAB/Simulink, and the simulation results are compared, concluding that the LQR control algorithm is the most optimal for balancing this model.