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This is a Experimental Study study.

October 19, 2025MachinesOpen Access

Self-Regulating Fuzzy-LQR Control of an Inverted Pendulum System via Adaptive Hyperbolic Error Modulation

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This innovative control framework enhances tracking accuracy in inverted pendulums, indicating improved disturbance rejection and robustness.

The proposed controller achieves a 41.8% reduction in pendulum angle variance, enhancing stability and performance.
Integration of fuzzy control with LQR using a linear decomposition function improves tracking error management significantly.
The adaptive modulation of compounded variables enhances robustness and minimizes oscillations for better control outcomes.
Experimental results confirm the controller's superior performance over baseline LQR and conventional fuzzy-LQR approaches.

Saleem et al. (2025) studied this question.

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This innovative control framework enhances tracking accuracy in inverted pendulums, indicating improved disturbance rejection and robustness.