Lectures related to Optimal Control and State Estimation

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

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

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

Explores Nonlinear Model Predictive Control, covering stability, optimality, pitfalls, and examples.

Covers the basics of state-space representation and explores transformations to different forms.

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

Covers the structure theorem for state-space representations and companion forms.

Explores the shift from continuous to discrete control systems, focusing on the challenges and benefits of digital implementation.

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

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

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

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

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

Covers the integration of control and estimation in dynamic systems.

Explores the significance of feedback mechanisms in visual intelligence and adaptation processes.

Covers stability, poles, zeros, and control in dynamic systems, emphasizing the importance of observability.

Discusses selecting pole locations in state-space control systems to meet time-domain specifications and minimize control effort.

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

Explores full state feedback control design, focusing on pole placement and linear state-feedback controller design for systems like a pendulum.

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