Lectures related to Control Theory Fundamentals

State-Space Representation: Structure Theorem

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

Covers the basic concepts of control theory and the selection of optimal controls.

State-Space Representation: Controllability and Observability

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

Controllability and Reachability

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

State-Space Representation: Basics & Transformations

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

Observability and Controllability

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

Stability of ODE

Explores the stability of Ordinary Differential Equations, focusing on solution dependence, critical data, linearization, and control of nonlinear systems.

Linear Systems Control: Fundamentals and Applications

Explores linear systems control fundamentals, controllability, and optimal control choices.

Controllability and Observability

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

Learning and Control for Complex Systems

Explores learning and control for complex systems, addressing challenges and opportunities in technology and interdisciplinary research.

Infinite-Horizon LQ Control: Solution & Example

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

Stability: Poles, Zeros, and Control

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

Linear Control Systems

Covers the reduction of complex systems to linear situations and controllability conditions.

Nonlinear Model Predictive Control

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

Balanced Realization: SISO Case

Covers the concept of balanced realization in the SISO case, focusing on system observability and controllability.

Linear Quadratic Optimal Control: Theory and Applications

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

Fault Simulation and Testability Analysis

Covers fault simulation, testability analysis, and fault list generation in VLSI systems.

SISO Polynomial Controllers: Sylvester Matrix, Internal Model Principle

Covers the design of SISO polynomial controllers using concepts such as the Sylvester matrix and model matching.

Multivariable Control: Weight Design and Stability Analysis

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

Symmetric Matrices and Quadratic Forms

Explores symmetric matrices, diagonalization, and quadratic forms properties.