Multivariable Control: System Theory and Linear Systems

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Explores control of dynamic systems, impulse response, Laplace transform, and Fourier transform for solving differential equations.

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

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

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

Explores the application of Laplace transform in state space modeling of linear systems and the control of dynamic systems.

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

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

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

Covers the theoretical basis of linear and nonlinear dynamical systems for engineers.

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