Lectures related to Preserving Movement Variability in Robotic Training

Covers the design and implementation of state observers and output-feedback controllers in multivariable control systems.

Discusses closed-loop eigenvalue selection and disturbance impact in multivariable control systems.

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

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

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

Covers the design of estimators and controllers for multivariable systems, focusing on state estimation and disturbance rejection.

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