Topic: Adaptive and Learning Control for Underactuated Systems

Underactuated systems are dynamic systems that possess fewer control inputs than degrees of freedom, making the control problem challenging and requiring innovative approaches to achieve desired performance.

In various fields such as robotics, aerospace, marine engineering, and many others, underactuated systems play a crucial role due to their inherent simplicity, efficiency, and ability to handle complex tasks with limited control resources. However, the control research for underactuated systems remains a significant area, with diverse applications demanding advanced control strategies that can adapt to uncertainties, disturbances, and changing environmental conditions.

The objective of this Special Issue is to gather state-of-the-art research contributions from leading experts and researchers in the field of adaptive and learning control for underactuated systems. The issue aims to shed light on the recent advancements, novel techniques, and theoretical developments that improve the control performance and efficiency of underactuated systems.

The scope of this Special Issue encompasses a wide range of topics related to adaptive and learning control for underactuated systems. These include, but are not limited to:
● Adaptive control algorithms for underactuated systems: The development of adaptive control schemes that enable underactuated systems to autonomously adapt their control strategies based on online observations, system identification, and parameter estimation;
● Learning-based control methods: The integration of machine learning, deep learning, and reinforcement learning techniques to enable underactuated systems to learn from experience and optimize their control policies;
● Robust control approaches: Techniques that enhance the robustness of underactuated systems against uncertainties, disturbances, model inaccuracies, and environmental variations;
● Trajectory/Path planning: Proposing learning-based trajectory/path planning methods for underactuated systems to adapt to complex environmental conditions;
● Control design for specific underactuated systems: Case studies and control design methodologies for specific underactuated systems such as unmanned aerial vehicles (UAVs), robotic manipulators, surface vessels, and other relevant applications;
● Designing and modeling of practical underactuated systems: Based on the practical requirements, design the detailed mechanical structure and actuating parts for a specific underactuated system, and solve the dynamic modeling problem for the designed system;
● Real-time implementation and experimental validation: Practical implementations, hardware-in-the-loop simulations, and experimental validations of adaptive and learning control strategies for underactuated systems.

31 Mar 2024