Neural Network Modeling and Control with Applications

Dear Colleagues,

This Special Issue focuses on "Neural Network Modeling and Control with Applications", aiming to present the latest advances in integrating neural network techniques with control theories for solving complex engineering and scientific problems. Neural networks have emerged as powerful tools for nonlinear system modeling and intelligent control, addressing challenges such as uncertainty, nonlinearity, and complexity in industrial automation, autonomous systems, and other critical fields. The scope of this Special Issue encompasses a broad range of cutting-edge research directions, including neural network-based modeling methods, nonlinear intelligent control, reinforcement learning control, and data-driven intelligent control. We welcome both theoretical studies that deepen the fundamental understanding of neural network-based modeling and control mechanisms and practical application papers that demonstrate the effectiveness of these techniques in real-world scenarios. By compiling high-quality contributions from researchers across the world, this Special Issue intends to establish an academic exchange platform, promote the in-depth fusion of neural network technology and control engineering, and provide important theoretical guidance and technical references for optimizing control strategies in autonomous systems, intelligent equipment, and other related fields. We aim to advance the innovation and industrial application of neural network modeling and control technologies.

Dr. Jiapeng Liu
Dr. Hailun Zhang
Guest Editors

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