Implicit Function Theorem: Estimates on the size of the domain

• Published in: arXiv.org
• Main Authors: Jindal, Ashutosh, Chatterjee, Debasish, Banavar, Ravi
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 06.07.2023
• Subjects: Computer Science - Systems and Control; Control theory; Discrete time systems; Domains; Estimates; Feedback linearization; Mathematical analysis; Numerical analysis; Numerical integration; Optimization; Robustness (mathematics); Theorems
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.2205.12661

In this article, we present explicit estimates of the size of the domain on which the Implicit Function Theorem and the Inverse Function Theorem are valid. For maps that are twice continuously differentiable, these estimates depend upon the magnitude of the first-order derivatives evaluated at the point of interest, and a bound on the second-order derivatives over a region of interest. One of the key contributions of this article is that the estimates presented require minimal numerical computation. In particular, these estimates are arrived at without any intermediate optimization procedures. We then present three applications in optimization and systems and control theory where the computation of such bounds turns out to be important. First, in electrical networks, the power flow operations can be written as Quadratically Constrained Quadratic Programs (QCQPs), and we utilize our bounds to compute the size of permissible power variations to ensure stable operations of the power system network. Second, the robustness margin of positive definite solutions to the Algebraic Riccati Equation (frequently encountered in control problems) subject to perturbations in the system matrices are computed with the aid of our bounds. Finally, we employ these bounds to provide quantitative estimates of the size of the domains for feedback linearization of discrete-time control systems.