Controllability and Reachability

Related lectures (32)

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

Covers Gaussian random variables, affine transformations, and linear systems driven by Gaussian noise in multivariable control.

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

Explores linear quadratic Gaussian control and the challenges of modeling errors in control systems.

Explores integral control, disturbance estimation, controller design, and observer design in multivariable control systems.

Explores stability and eigenvalues of LTI systems, reachability, and controllability of dynamical systems.

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

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

Explores the linearized and extended Kalman Filters, illustrating their application in nonlinear systems and the estimation of unknown parameters.

Covers Data-Driven Control methods and applications in various fields, emphasizing robustness and performance.

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

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

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