The field of control systems is moving towards the development of more sophisticated and robust safety-critical control methods. Recent research has focused on the creation of novel frameworks and techniques for ensuring safety and stability in complex systems, including those with nonlinear dynamics and uncertain parameters. One notable trend is the use of control barrier functions (CBFs) and model predictive control (MPC) to guarantee safety and performance in systems such as autonomous vehicles, robotics, and aerospace applications. Additionally, advancements in adaptive systems have led to the development of new parameter estimation laws and adaptive optimal control methods that can handle uncertain systems and ensure safety and convergence. Noteworthy papers in this area include:

• Lagrange-Poincare-Kepler Equations of Disturbed Space-Manipulator Systems in Orbit, which presents a novel framework for modeling the dynamics of spacecraft-manipulator systems.
• Spatiotemporal Tubes based Control of Unknown Multi-Agent Systems for Temporal Reach-Avoid-Stay Tasks, which introduces a controller for unknown dynamical multi-agent systems to achieve temporal reach-avoid-stay tasks.
• Safe Output-Feedback Adaptive Optimal Control of Affine Nonlinear Systems, which develops a safe control synthesis method that integrates state estimation and parameter estimation within an adaptive optimal control architecture.