Lectures related to StateSpace Controllability

State-Space Representation: Controllability and Observability

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

State-Space Representation: Structure Theorem

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

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.

Controllability and Reachability

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

Controllability and Observability

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

StateSpace ControlDesign

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

State Space Control: Discrete Systems

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

Fault Simulation and Testability Analysis

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

Control Theory Fundamentals

Introduces control theory fundamentals, including controllability and invertibility of systems.

Multivariable Control: Eigenvalue Assignment and Ackermann's Formula

Explores control problems, eigenvalue assignment, and canonical controllability form for single-input systems.

Stability: Poles, Zeros, and Control

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

Built-In Self-Test (BIST): Techniques and Implementations

Explores Built-In Self-Test (BIST) techniques in VLSI systems, covering benefits, drawbacks, implementation details, and the use of Linear Feedback Shift Registers (LFSRs) for test pattern generation.

Eigenvalue Assignment in Multivariable Control

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

Exact and Approximate Sampling in Multivariable Control

Explores exact and approximate sampling in multivariable control systems, discussing stability, eigenvalues, and system properties.

StateSpace Pole Locations

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

Control Theory Fundamentals

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

Observability and Duality

Delves into the observability of LTI systems, covering controllability, duality, and observability tests.

Multivariable Control: Weight Design and Stability Analysis

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

Markov Decision Processes: Foundations of Reinforcement Learning

Covers Markov Decision Processes, their structure, and their role in reinforcement learning.