Lectures related to Observer Design

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

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

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

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

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

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

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

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

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

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

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

Covers the design of a regulator and state estimator for optimal control.

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

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

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

Explores observability and controllability in linear systems, emphasizing the significance of input decoupling for observability.

Covers controllability and observability in linear systems, discussing necessary conditions and implications of unimodular matrices.

Delves into the impact of quantization on networked control systems, exploring stability, performance, and design trade-offs.

Covers course organization, system control, dynamics, artificial intelligence, water cycles, and sea currents.

Explores Eigenvalue Assignment in multivariable control, emphasizing the effects of discretization and the challenges in preserving system structure.