Covers model predictive control for multi-region Macroscopic Fundamental Diagrams in traffic flow modeling and its application in handling non-linear control problems.
Introduces Data-Enabled Predictive Control (DEEPC) as a method to design controllers directly from measured input/output data, reducing the cost of design and commissioning.
Explores safe learning in robotics, covering the state of the art, open challenges, and vision in the field, emphasizing the importance of interdisciplinary collaboration.
Covers the computation of cost function for multivariable control systems using the LQR framework and applying gradient descent for controller improvement.
