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Control Design for Iterative Methods in Solving Linear Algebraic Equations

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In the interaction between control and mathematics, mathematical tools are fundamental for all control methods, but it is unclear how control impacts mathematics. This article attempts to give an answer… Click to show full abstract

In the interaction between control and mathematics, mathematical tools are fundamental for all control methods, but it is unclear how control impacts mathematics. This article attempts to give an answer with focus on solving linear algebraic equations (LAEs) from the perspective of systems and control. By proposing an iterative method that integrates a learning control mechanism, a class of tracking problems for iterative learning control (ILC) is explored for the problem solving of LAEs. A trackability property of ILC is newly developed, by which analysis and synthesis results are established to disclose the equivalence between the solvability of LAEs and the controllability of discrete control systems. Hence, LAEs can be solved by equivalently achieving the perfect tracking tasks of resulting ILC systems via the classic state feedback-based design and analysis methods. It is shown that the solutions for any solvable LAE can all be calculated with different selections of the initial input. Moreover, the presented ILC method is applicable to determining all the least squares solutions of any unsolvable LAE. In particular, a deadbeat design is incorporated to ILC such that the solving of LAEs can be completed within finite iteration steps. The trackability property is also generalized to conventional two-dimensional ILC systems, which creates feedback-based methods, instead of commonly known contraction mapping-based methods, for the design and convergence analysis of ILC.

Keywords: solving linear; ilc; control; design; linear algebraic; algebraic equations

Journal Title: IEEE Transactions on Automatic Control
Year Published: 2022

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