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Focuses on designing reduced-order observers in multivariable control systems, emphasizing the importance of observers and eigenvalue assignment in controller design.
Covers the computation of cost function for multivariable control systems using the LQR framework and applying gradient descent for controller improvement.
Explores the Extended Kalman Predictor algorithm and the linearized Kalman Filter for multivariable control systems, discussing the challenges and applications.
