Lectures related to Optimal Control: OCPs

Focuses on numerical modelling of atmospheric processes to predict weather and climate phenomena, covering key concepts and methods.

Covers numerical differentiation, forward differences, Taylor's expansion, Big O notation, and error minimization.

Explores advanced space discretization techniques in numerical analysis for solving differential systems efficiently and accurately.

Explores Nonlinear Model Predictive Control principles, stability analysis, design steps, and practical considerations.

Explores controlled stochastic processes, focusing on analysis, behavior, and optimization, using dynamic programming to solve real-world problems.