Concept

State-space representation

Related lectures (32)

State-Space Representation: Basics & Transformations

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

State-Space Representation: Controllability and Observability

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

StateSpace ControlCanonical: Canonical Forms

Covers control canonical form, state transformations, and full state feedback control.

State Space Representation: Models

Covers the state-space representation of systems and models in process control.

State-Space Representation: Structure Theorem

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

Optimal Control and State Estimation

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

Observability in Multivariable Control

Explores observability in multivariable control systems and the PBH test for system reachability.

State Space Control: Discrete Systems

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

Observability and Controllability

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

Eigenvalue Assignment in Multivariable Control

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

Multivariable Control: System Theory and Applications

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

Observability and Governability

Explores observability, governability, state regulators, and canonical forms in dynamic systems.

Linearization Method: Examples

Covers the linearization method through two examples in process control.

StateSpace Pole Locations

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

Balanced Realization: SISO Case

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

Multivariable Control: Eigenvalue Assignment and Ackermann's Formula

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

Multivariable Control: State-Feedback and Eigenvalue Assignment

Covers state-feedback controller design for multivariable systems and discusses simplified methods for MIMO systems.

StateSpace ControlDesign

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

Introduction to Multivariable Control

Covers the basics of multivariable control, including system modeling, temperature control, and optimal strategies, emphasizing the importance of considering all inputs and outputs simultaneously.

State Representation and System Dynamics

Covers the representation of state-space models and system dynamics.