We study a class of hyperbolic partial differential equations on a one dimensional spatial domain with control and observation at the boundary. Using the idea of feedback we show these systems are well-posed in the sense of Weiss and Salamon if and only if the state operator generates a C 0-semigroup. Furthermore, we show that the corresponding transfer function is regular, i.e., has a limit for s going to infinity.

The Linear-Quadratic (LQ) optimal control problem is studied for aclass of first-order hyperbolic partial differential equation modelsby using a nonlinear infinite-dimensional (distributed parameter) Hilbert state-spacedescription. First the dynamical properties of the linearized modelaround some equilibrium profile are studied. Next the LQ-feedbackoperator is computed by using the corresponding operator Riccatialgebraic equation whose solution is obtained via a relatedmatrix Riccati differential equation in the space variable. Then thelatter is applied to the nonlinear model, and the resultingclosed-loop system dynamical performances are analyzed.

We derive absolute stability results of Popov-type for infinite-dimensional systems in an input-output setting. Our results apply to feedback systems where the linear part is the series interconnection of an $L^2$-stable linear system and an integrator, and the non-linearity satisfies a sector condition which allows for non-linearities with lower gain equal to zero (such as saturation, or more generally, bounded non-linearities). These results are used to prove convergence and stability properties of low-gain integral feedback control applied to $L^2$-stable linear systems subject to actuator and sensor non-linearities. The class of actuator/sensor non-linearities under consideration contains standard non-linearities which are important in control engineering such as saturation and deadzone. Moreover, we use the input-output theory developed to derive state-space results on absolute stability and low-gain integral control for strongly stable well-posed infinite-dimensional linear systems.