This article is concerned with the feedback stabilization for linear delay systems. The convergence of the numerical method in the literature is proved. Furthermore, the analytic gradient formula of the objective function is given. Numerical examples are given to illustrate the effectiveness of the presented result.
We consider the column sparsity of the feedback stabilization gain matrix in high-order linear systems. By means of a special matrix norm and the state transition matrix quadratic cost function (SQF) of the systems, the sparse feedback stabilization controller design problem is formulated as a regularized SQF optimization problem. We further derive the proximal mapping of the special matrix norm, and then based on the gradient descent of the SQF part of the objective function, the proximal gradient method is introduced to develop an algorithm for solving the non-smooth optimization problem. Numerical examples are given to illustrate the effectiveness of the proposed method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.