Focuses on designing reduced-order observers in multivariable control systems, emphasizing the importance of observers and eigenvalue assignment in controller design.
Explores the time-varying Kalman filter, state estimation, challenges in conditioning on measured outputs, and the importance of affine transformations.
Covers the basics of multivariable control, including system modeling, temperature control, and optimal strategies, emphasizing the importance of considering all inputs and outputs simultaneously.
