Multivariable Control: Linear Quadratic Gaussian Control

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Explores state estimation and Kalman filtering for multivariable control systems, with applications in communication channels and vehicle navigation.

Explores learning and control for complex systems, addressing challenges and opportunities in technology and interdisciplinary research.

Explores the handling of correlated noise in multivariable control systems, emphasizing the Kalman Filter's adaptation and performance evaluation.

Discusses the design of weighting matrices for LQR and Gaussian random vectors.

Discusses the steady-state Kalman predictor, provides examples, and compares Luenberger and Kalman filtering.

Covers innovation-based tests for Kalman filtering, LQG control, and the linearized Kalman filter.

Covers the proof of the recursive formula for the optimal gains in LQ control over a finite horizon.

Explores the Model Reference Method for designing PID regulators and cascade controllers for complex systems.

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

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