Optimal control theory is a fascinating topic, one that has not always received the recognition it deserves. Researchers and practitioners in this field have had to rely on dated, theory-heavy text books and their own research, while topics such as SDRE and 0 - D, which have multiple technical applications, have not been readily available in text book format.
Applied Optimal Control and State Estimation is a timely and comprehensive advanced text, aimed at students and professional engineers. A single source of up-to-date information, the book covers all the basics and essentials of optimal control theory and state estimation, the fundamental and classical aspects of optimal control design, and highlights recent and important advances in optimal control theory. While the book presents the theory and background, it also concentrates on real time applications of advanced optimal control techniques such as Classical numerical solution of Two-point boundary value problems; Linear Quadratic Regulator (LQR) design; State Dependent Riccati Equation (SDRE) design; design; Sufficiency condition and neighbouring optional control; Dynamic programming; Transcription Method including conventional as well as the advanced Pseudo-spectral transcription; Model Predictive Control (MPC); Model Predictive Static Programming (MPSP) and its variants; Optimal Control of Distributed Parameter Systems; Linear Quadratic Observer; Basics of Random variables; Optimal State Estimation using Kalman Filter (KF), including variants; Extended Kalman Filter (EKF); Unscented Kalman Filter (UKF); Robust control design through optimal control and state estimation; and Stochastic Optimal Control.