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About

Miaolei Zhou is a leading researcher in precision motion control and intelligent systems, with a focus on nonlinear dynamics and smart material actuators. Her work bridges advanced control theory and practical mechatronics, particularly for micro-positioning and autonomous robotics. Zhou’s most cited paper (2023, 18 citations) introduces a novel sliding mode iterative learning control with an iteration-dependent parameter mechanism, significantly improving convergence performance for piezoelectric-actuated micro-positioning stages—a critical contribution to high-precision manufacturing and biomedical devices. She also developed a Hopfield neural network-based Bouc-Wen model (2020, 13 citations) to address asymmetrical rate-dependent hysteresis in magnetic shape memory alloy actuators, enabling more reliable performance in aerospace and robotics applications. Earlier in her career, Zhou advanced autonomous navigation for outdoor mobile robots, integrating multi-sensor fusion (GPS, laser rangefinders, encoders) with extended Kalman filtering to reduce dead-reckoning errors (2014, 4 citations). Her work on multi-sensor data acquisition systems (2011, 3 citations) laid foundational tools for real-world robotic autonomy. With a growing citation impact, Zhou’s research is pivotal for next-generation precision actuators and intelligent robotic systems, making her a key figure in nonlinear control and smart materials.