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

A special issue of Actuators (ISSN 2076-0825). This special issue belongs to the section "Control Systems".

Deadline for manuscript submissions: 15 June 2026 | Viewed by 10

Special Issue Editor


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Guest Editor
Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan City, Taiwan
Interests: linear/nonlinear control system analysis and design; system modeling and parameter identification; sliding mode control and its applications; adaptive control and its applications; servo mechanism integration and control technology; servo motor motion controls; path planning and trajectory interpolation; unmanned aerial vehicle control design; control system design using artificial intelligence intelligent indoor perception; localization and mapping technology
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Special Issue Information

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

Manuscript Submission Information

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Keywords

  • system modeling and parameter identification
  • linear/nonlinear control design
  • sliding mode control (SMC) systems
  • model reference adaptive control (MRAC) systems
  • proportional–integral–derivative (PID) control
  • robust observer design for disturbance/state estimation
  • sensor-fusion-based control technology
  • servo mechanism control design and applications
  • artificial intelligence (AI)-based technology for control systems
  • system digital twin modeling for diagonisis and control decision-making
  • path planning and optimization
  • control design of unmanned aerial vehicles (UAVs)
  • advanced control applications and optimization
  • robot control, navigation, localization, and mapping

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