Multivariable Control: Equilibria and Stability Analysis

Related lectures (31)

Explores the properties and examples of diagonalizable matrices, emphasizing the relationship between eigenvectors and eigenvalues.

Covers equilibria, stability analysis, and Lyapunov theory in linear systems, focusing on eigenvalues and stability properties.

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

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

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

Explores eigenvalues, stability, eigenvectors, and error estimation techniques in linear systems.

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.

Covers the diagonalization of matrices using eigenvectors and eigenvalues.

Explores stability, reachability, and controllability in linear systems, emphasizing their significance in system analysis.

Covers the design and implementation of state observers and output-feedback controllers in multivariable control systems.

Covers the Singular Value Decomposition (SVD) in detail, including properties of matrices and system linearity.

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