Advanced Control of Complex Dynamical Systems and Robotics with Applications

Dear Colleagues,

This Special Issue showcases the latest research on the use of mathematical models and methods in the analysis and control of complex dynamical systems and robots.

These articles explore a range of topics, including nonlinear dynamics, adaptive control, optimal control, distributed control, and learning control. They present new theoretical results and practical applications that demonstrate the dynamics and control of complex systems and robots.

Specific applications of these techniques in different complex systems and robotic domains are addressed. The topics include the following:

• The modelling and control of nonlinear systems using differential geometry and Lie group methods;
• Designing adaptive controllers for uncertain systems using Lyapunov stability theory and sliding mode control techniques;
• Robotic systems using optimal control theory and numerical optimization methods;
• Learning control policies for autonomous robots using machine learning algorithms and reinforcement learning techniques;
• Learning cross-domain knowledge for robotic interaction and comprehension using machine learning algorithms and large pretrained language models.

We hope this Special Issue will serve as a valuable resource for researchers and practitioners interested in this field. The articles provide a glimpse into the diverse range of mathematical techniques that can be applied to these fields while also highlighting the importance of collaboration between mathematicians and engineers in addressing real-world challenges.

Dr. Gang Wang
Prof. Dr. Chaoli Wang
Prof. Dr. Qingdu Li
Guest Editors

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