A Comparative Analysis of Intelligent Control Approaches for the Ball-and-Plate Problem
DOI:
https://doi.org/10.15282/mekatronika.v6i2.10977Keywords:
Ball-and-Plate, Proportional-Integral-Derivative, Model Predictive Control, Sliding Mode Control, Linear Quadratic Regulator, Fuzzy Logic ControlAbstract
This paper conducts a comprehensive comparative analysis of five intelligent control approaches applied to the Ball-and-Plate problem, evaluating their performance based on Step Response metrics and Trajectory Tracking Mean Absolute Error (MAE). The techniques examined include Proportional-Integral-Derivative (PID), Linear Quadratic Regulation (LQR), Model Predictive Control (MPC), Sliding Mode Control (SMC), and Fuzzy Logic Control (FLC). Through rigorous experimentation and analysis, each technique’s strengths and weaknesses are identified, with MPC and SMC emerging as superior options in terms of response time and trajectory tracking accuracy, notably achieving zero overshoot and minimal errors. LQR exhibits exceptionally fast response times, while PID and FLC offer moderate performance. The study’s findings provide valuable insights for selecting appropriate control techniques tailored to specific application requirements and suggest avenues for future research, including the exploration of hybrid control approaches and adaptive control algorithms to enhance system robustness and reliability in addressing the Ball-and-Plate problem.
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