The field of autonomous systems and control is rapidly evolving, with a focus on developing innovative methodologies for controlling and navigating complex systems. Recent research has explored the use of hierarchical sliding mode control, event-triggered nonlinear model predictive control, and modular energy-aware frameworks for multicopter modeling. These approaches aim to improve the stability, efficiency, and safety of autonomous systems, such as quadrotors and robotic systems. Noteworthy papers include the introduction of a novel event-triggered distributed nonlinear model predictive control method for cooperative transportation, and the development of a modular energy-aware framework for multicopter modeling. Additionally, research has been conducted on adaptive control methods, such as input-output feedback linearization-based adaptive control, and data-driven fuzzy control for time-optimal aggressive trajectory following. These advancements have the potential to significantly impact various applications, including surveillance, monitoring, inspection, and search and rescue missions.
Advancements in Autonomous Systems and Control
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A Class of Hierarchical Sliding Mode Control based on Extended Kalman filter for Quadrotor UAVs
Event-Triggered Nonlinear Model Predictive Control for Cooperative Cable-Suspended Payload Transportation with Multi-Quadrotors
A Modular Energy Aware Framework for Multicopter Modeling in Control and Planning Applications
Energy Aware and Safe Path Planning for Unmanned Aircraft Systems
Deep Learning-Enhanced Robotic Subretinal Injection with Real-Time Retinal Motion Compensation
Learning Flatness-Preserving Residuals for Pure-Feedback Systems
Reducing the Communication of Distributed Model Predictive Control: Autoencoders and Formation Control
Ultrasound-Guided Robotic Blood Drawing and In Vivo Studies on Submillimetre Vessels of Rats
Adaptive Multirobot Virtual Structure Control using Dual Quaternions
Adaptive Control of Dual-Rotor Rotational System with Unknown Geometry and Unknown Inertia
Control-Oriented Modelling and Adaptive Parameter Estimation for Hybrid Wind-Wave Energy Systems
Data-driven Fuzzy Control for Time-Optimal Aggressive Trajectory Following