Analysis and Design of Linear/Nonlinear Control System—2nd Edition

Dear Colleagues,

The field of control systems engineering has entered a new era driven by artificial intelligence (AI) and data-driven technologies. This Special Issue aims to gather pioneering research that advances both the theoretical foundations and practical realizations of intelligent control systems across linear, nonlinear, and complex dynamic environments. Topics of interest include model-based and model-free control, adaptive, sliding mode and robust control, learning-based and neural control, and hybrid AI-control frameworks. Emphasis will be placed on how modern AI techniques, such as reinforcement learning, deep learning, evolutionary optimization, and digital twin technologies, can enhance system autonomy, adaptability, and control decision-making capabilities. Contributions that bridge theory with real-world implementation, propose novel algorithms, or present comprehensive reviews of intelligent control trends are especially encouraged. This Special Issue will serve as a platform for researchers and practitioners to share breakthroughs that accelerate the convergence of control theory, computation, and artificial intelligence, shaping the next generation of smart, resilient, and self-evolving control systems across various industries.

Dr. Chao-Chung Peng
Guest Editor

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