Advancements in Control Systems and Robotics: Safety, Stability, and Adaptability

The recent publications in the field of control systems and robotics highlight a significant trend towards enhancing safety, stability, and adaptability in complex dynamic environments. A common theme across these studies is the integration of advanced control strategies, such as Lyapunov-based methods, Control Barrier Functions (CBFs), and adaptive feedback linearization, to address challenges posed by unknown dynamics, disturbances, and measurement inaccuracies. Innovations in observer design and state estimation techniques are also prominent, enabling more accurate and robust control solutions. Furthermore, the application of meta-learning and neural networks for system modeling and control synthesis represents a forward-looking approach to handling system uncertainties and improving control performance. The emphasis on safety-critical control, particularly in robotic systems and spacecraft servicing, underscores the field's commitment to ensuring operational safety and reliability in high-stakes applications.

Noteworthy Papers

  • Proxy Control Barrier Functions: Introduces a novel scheme integrating barrier-based and Lyapunov-based safety-critical control, broadening the applicability of CBF-based methods.
  • Collaborative Spacecraft Servicing: Develops a distributed state estimation and tracking framework for spacecraft servicing under partial state information, eliminating the need for expensive velocity sensors.
  • A Novel Observer Design for LuGre Friction Estimation and Control: Presents a simple and standalone observer for estimating and compensating LuGre friction, enhancing tracking performance.
  • Coordinated Control of Deformation and Flight for Morphing Aircraft: Utilizes meta-learning and coupled state-dependent Riccati equations for the coordinated control of morphing aircraft, demonstrating efficacy through simulation.
  • Safe Circumnavigation of a Hostile Target: Proposes a novel control law for safe circumnavigation around a hostile target, ensuring stability and safety through barrier Lyapunov functions.

Sources

Proxy Control Barrier Functions: Integrating Barrier-Based and Lyapunov-Based Safety-Critical Control Design

Study of Frictional and Impact Transients in Active-Passive Mechanical Pair

Collaborative Spacecraft Servicing under Partial Feedback using Lyapunov-based Deep Neural Networks

A Novel Observer Design for LuGre Friction Estimation and Control

Coordinated Control of Deformation and Flight for Morphing Aircraft via Meta-Learning and Coupled State-Dependent Riccati Equations

Pitch Plane Trajectory Tracking Control for Sounding Rockets via Adaptive Feedback Linearization

Formally Verified Neural Lyapunov Function for Incremental Input-to-State Stability of Unknown Systems

Safe Circumnavigation of a Hostile Target Using Range-Based Measurements

IEEE_TIE25: Analysis and Synthesis of DOb-based Robust Motion Controllers

Range-Only Dynamic Output Feedback Controller for Safe and Secure Target Circumnavigation

Some remarks on practical stabilization via CLF-based control under measurement noise

Reducing real-time complexity via sub-control Lyapunov functions: from theory to experiments

Safety-Critical Control for Discrete-time Stochastic Systems with Flexible Safe Bounds using Affine and Quadratic Control Barrier Functions

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