What question did this study set out to answer?

The aim is to develop a real-time adaptive LQR control strategy for improving performance in rotary inverted pendulums.

February 28, 2026Mathematical and Computational ApplicationsOpen Access

Real-Time Adaptive Linear Quadratic Regulator Control for the QUBE–2 Rotary Inverted Pendulum

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Authors

CLCynthia Lopez-JordanColumbus State University MJMohammad JafariColumbus State University

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Implication

Experimental validation of an adaptive LQR control strategy improves tracking accuracy and reduces control effort in inverted pendulums, suggesting enhanced performance in real-time systems.

Key Points

The aim is to develop a real-time adaptive LQR control strategy for improving performance in rotary inverted pendulums.
Continuous adaptation of the LQR state weighting matrix based on real-time feedback.
Implementation using a continuous-time Riccati differential equation.
Experimental validation on QUBE-Servo 2 platforms under various reference trajectories.
Comparison against fixed-gain LQR controllers using multiple performance metrics.
Achieved over 70–90% reduction in tracking error metrics.
Over 94% reduction in control effort compared to fixed-gain LQR.
Demonstrated effective dynamic reshaping of LQR controller behavior.

Cite This Study

Lopez-Jordan et al. (2026) studied this question.

synapsesocial.com/papers/69a288060a974eb0d3c0402e https://doi.org/10.3390/mca31020033

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Implication

Experimental validation of an adaptive LQR control strategy improves tracking accuracy and reduces control effort in inverted pendulums, suggesting enhanced performance in real-time systems.

Real-Time Adaptive Linear Quadratic Regulator Control for the QUBE–2 Rotary Inverted Pendulum

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Implication

Key Points

Cite This Study

Real-Time Adaptive Linear Quadratic Regulator Control for the QUBE–2 Rotary Inverted Pendulum

Discussion

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Implication

Key Points

Cite This Study

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