This book presents the separation principle which is also known as the principle of separation of estimation and control and states that, under certain assumptions, the problem of designing an optimal feedback controller for a stochastic system can be solved by designing an optimal observer for the system's state, which feeds into an optimal deterministic controller for the system. Thus, the problem may be divided into two halves, which simplifies its design. In the context of deterministic linear systems, the first instance of this principle is that if a stable observer and stable state feedback are built for a linear time-invariant system (LTI system hereafter), then the combined observer and feedback are stable. The separation principle does not true for nonlinear systems in general. Another instance of the separation principle occurs in the context of linear stochastic systems, namely that an optimum state feedback controller intended to minimize a quadratic cost is optimal for the stochastic control problem with output measurements. The ideal solution consists of a Kalman filter and a linear-quadratic regulator when both process and observation noise are Gaussian. The term for this is linear-quadratic-Gaussian control. More generally, given acceptable conditions and when the noise is a martingale (with potential leaps), a separation principle, also known as the separation principle in stochastic control, applies when the noise is a martingale (with possible jumps).

This book uses H control methods to study robust state estimation and Lagrange stabilization of sector bounded nonlinear systems. Part A developed a new approach for constructing a robust state estimator for uncertain stochastic systems with slope-bounded nonlinearities satisfying IQC and multipliers are used to exploit the uncertainties and nonlinearities. Part B studies stability analysis and Lagrange stabilization of pendulum-like systems. This part proposes two Lagrange stability criteria which can be applied to more general pendulum-like systems. These results, with a sufficient condition for pendulum-likeness, enable Lagrange stabilization of pendulum-like systems with multiple nonlinearities to be formulated and solved in term of the solutions to game-type Riccati equations. This book generalizes some results in standard H control. An extended strict bounded real lemma and a pseudo H control theory are developed. The latter includes a pseudo strict bounded real lemma which relates a pseudo H condition to the existence of a sign indefinite solution to a ARE. These results can handle some control design problems which the standard H control theory is not applicable.

This eagerly awaited follow-up to Nonlinear Control Systems incorporates recent advances in the design of feedback laws, for the purpose of globally stabilizing nonlinear systems via state or output feedback. The author is one of the most prominent researchers in the field.