Novel Results on Output-Feedback LQR Design

This article provides novel developments in output-feedback stabilization for linear time-invariant systems within the linear quadratic regulator (LQR) framework. First, we derive the necessary and sufficient conditions for output-feedback stabilizability in connection with the LQR framework. Then, we propose a novel iterative Newton's method for output-feedback LQR design and a computationally efficient modified approach that requires solving only a Lyapunov equation at each iteration step. We show that the proposed modified approach guarantees convergence from a stabilizing state feedback to a stabilizing output-feedback solution and succeeds in solving high-dimensional problems where other, state-of-the-art methods, fail. Finally, numerical examples illustrate the effectiveness of the proposed methods.

Automated summary

This article presents novel developments in output-feedback stabilization for linear time-invariant systems within the framework of linear quadratic regulator (LQR). The necessary and sufficient conditions for output-feedback stabilizability are derived, followed by the proposal of a novel iterative Newton's method and a computationally efficient modified approach. The proposed modified approach guarantees convergence from a stabilizing state feedback to a stabilizing output-feedback solution and successfully solves high-dimensional problems. Numerical examples demonstrate the effectiveness of the proposed methods.