Miroslav Krstic

A look into modern techniques for controlling complex systems over time and space.

This research explores gain scheduling and neural operators for better control of nonlinear PDEs.

Innovative approach using neural networks to stabilize PDE systems efficiently.

A standardized platform for testing learning algorithms in boundary control of partial differential equations.

This article examines feedback control methods for efficient tank-liquid management.

Neural networks are enhancing control systems for managing complex reaction-diffusion processes.

A look into performance-barrier event-triggered control in reaction-diffusion systems.

Learn how robotic manipulators work and their applications in our world.