A Study of Adaptive Model Predictive Control for Rotary Inverted Pendulum
DOI:
https://doi.org/10.59247/jfsc.v3i2.302Keywords:
Rotary Inverted Pendulum, Adaptive Control, Model Predictive Control, Kalman Filter, Linear Time-varyingAbstract
This paper proposes an Adaptive Model Predictive Control (MPC) approach for the rotary inverted pendulum (RIP). The method combines Linear Time-Varying (LTV) models at each sampling instant with a Linear Time-Varying Kalman Filter (LTVKF) for state estimation. By predicting and adapting to dynamic system changes, the controller achieves trajectory tracking performance comparable to non-adaptive MPC. However, the Adaptive MPC extends the arm’s operating range by up to 1.5 times, making it a promising solution for strongly nonlinear or time-varying systems like the RIP.
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Copyright (c) 2025 Phuc-Hoang Huynh, Khac-Chan-Nguyen Le, Truong-Phuc Nguyen, Hoang-Dang-Khoa Tran, Su-Truong Dang, Thanh-Quyen Nguyen, Thang-Phong Le, Huu-Hanh Nguyen, Pham-Hong-Linh Tran, Hau-Phuong Nguyen, Hoang-Son Nguyen, Tai-Truong Nguyen, Hai-Thanh Nguyen
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