Precision Machining Optimization: Fuzzy Logic and Adaptive Control

Dear Colleagues,

With the continuous demand for higher accuracy, efficiency and reliability in advanced manufacturing, precision machining has become a cornerstone technology in aerospace, optics, semiconductor manufacturing, biomedical devices and ultra-precision instrumentation. However, modern precision machining processes are increasingly challenged by nonlinear dynamics, strong coupling effects, time-varying uncertainties and multi-source disturbances arising from tool wear, material heterogeneity, thermal deformation and environmental fluctuations.

Traditional model-based control and optimization methods often rely on simplified assumptions and accurate system models, which are difficult to obtain in real machining environments. As a result, intelligent control strategies—particularly fuzzy logic–based methods and adaptive control techniques—have attracted growing attention due to their strong robustness, flexibility and capability to handle uncertainty, nonlinearity and incomplete information. Fuzzy logic provides an effective framework for incorporating expert knowledge and qualitative reasoning into machining control and decision-making, while adaptive control enables real-time parameter adjustment and performance optimization under varying operating conditions. The integration of these approaches offers promising solutions for achieving high-precision, high-efficiency and stable machining processes.

This Special Issue aims to bring together recent advances in the modeling, monitoring, optimization and control of precision machining processes, with a particular focus on fuzzy logic, adaptive control and their hybrid implementations. Contributions addressing both theoretical developments and practical applications are welcome.

Dr. Pengyue Zhao
Dr. Kaijie Zhu
Guest Editors

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