Hybrid Fuzzy-State Feedback Control for Fast Mechatronic Systems: Modeling and Experimental Validation on a Rotary Inverted Pendulum

Abstract

This paper introduces a general control framework for fast mechatronic systems that integrates linearized state-space control with nonlinear fuzzy logic strategies. The approach is applied to the Rotary Inverted Pendulum (RIP), a benchmark system characterized by rapid dynamics and strong nonlinearity. The system’s equations of motion are derived using the Euler-Lagrange method and linearized around the upright equilibrium point to design a state-feedback controller via the Linear Quadratic Regulator (LQR). To manage the system’s nonlinear behavior during the swing-up phase and near-region transitions, a fuzzy logic controller is incorporated, dynamically tuning the control effort based on the pendulum’s angular position and velocity. This hybrid scheme allows the linear controller to dominate where approximation is valid, while the fuzzy logic system handles broader, nonlinear dynamics. The full control architecture is implemented in LabVIEW and experimentally validated on the NI ELVIS II platform. Both simulation and hardware results show notable improvements in settling time, energy efficiency, and robustness. The proposed framework demonstrates high applicability to the control of fast-response mechatronic systems operating under mixed linear and nonlinear systems.