Lectures related to Nonlinear Model Predictive Control

Covers the proof of the recursive formula for the optimal gains in LQ control over a finite horizon.

Covers the principles of feedback control systems and their applications in various fields.

Explores the Model Reference Method for designing PID regulators and cascade controllers for complex systems.

Explores Infinite-Horizon Linear Quadratic (LQ) optimal control, emphasizing solution methods and practical examples.

Explores Linear Quadratic optimal control theory, covering FH-LQ and IH-LQ problems and the importance of observability in control systems.

Explores weight design and stability analysis in multivariable control systems, emphasizing Lyapunov theory and LQR stability.

Explores state-space representation, controllability, observability, and regulator calculation using the Ackermann method.

Covers state representation, controller design, LQR controllers, and optimal control criteria.

Covers system theory, classic feedback control, and applications in green building and natural gas refrigeration plants.

Explores Linear Quadratic optimal control, analyzing cost, and presenting the solution to the FH-LQ problem.

Covers the synthesis in the Bode diagram, dynamic controls, and the link between the Bode and Nyquist diagrams.

Covers the design of observers in control systems and the computation of state feedback controllers.

Explores Networked Control Systems, addressing packet dropouts, network delays, stability, and control laws for system boundability.

Explores stability, sensitivity, tracking performance, and regulation error in control systems.

Explores compensation of transmission delays in remote-control settings to ensure stability in networked control systems.

Explores reachability and controllability in multivariable control systems, discussing tests, proofs, and their implications.

Explores closed-loop control systems, PID regulator design, and performance analysis.

Covers BIBO stability, Lyapunov stability, state feedback, and eigenvalue assignment.

Explores system identification, stability criteria, and challenges in stabilizing cameras on moving platforms.