Quang-Thien Nguyen, Huynh-Phuc Le, Quoc-Kiet Dinh, Dieu-Minh-Thu Tran, Thi-Thanh-Hoang Le *
Ho Chi Minh City University of Technology and Education (HCMUTE)
Vo Van Ngan Str., No. 01, Ho Chi Minh City (HCMC), Vietnam
* Corresponding author. E-mail: hoangltt@hcmute.edu.vn
Robotica & Management, Vol. 30, No. 1, pp. 12-17
DOI: https://doi.org/10.24193/rm.2025.1.2
Abstract: This paper presents simulation of Sliding Mode Control (SMC) algorithm and the PID algorithm applied to the ball in tube – a single input single output (SISO) nonlinear system. The primary objective of this study is to stabilize the position of the ball at a desired location inside the tube despite disturbances or variations in initial conditions. Firstly, we focus on designing PID controller, the PID parameters are tuned using standard methods to ensure acceptable transient and steady – state performance. Thence, we proceed to design the Sliding Mode Controller and optimize it by using genetic algorithm (GA) to determine the optimal parameters for the controller, so that the system output can accurately track the desired setpoint. Through a series of simulations are carried out in Matlab/Simulink toevaluate the effectiveness of both controllers. Performance metrics such as rise time, settling time, overshoot, and steady-state error are used for comparison. The simulation results demonstrate that the GA-optimized SMC significantly outperforms the conventional PID controller in terms of tracking accuracy, robustness to disturbances, and control efficiency. These findings highlight the potential of intelligent optimization techniques like GA in enhancing the performance of advanced control algorithms such as SMC in nonlinear dynamic systems.
Keywords: PID Control; sliding mode control; ball in tube; SISO system.
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