Hierarchy of Quadratic Lyapunov Functions for Linear Time-Varying and Related Systems

被引:0
|
作者
Abdelraouf, Hassan [1 ]
Feron, Eric [2 ]
Klett, Corbin [3 ]
Abate, Matthew [4 ]
Coogan, Samuel [5 ]
机构
[1] Univ Illinois, Aerosp Engn, Champaign, IL 61820 USA
[2] King Abdullah Univ Sci & Technol, Dept Comp Elect & Math Sci & Engn, Thuwal 239556900, Saudi Arabia
[3] Georgia Inst Technol, Sch Aerosp Engn, Atlanta, GA 30332, Georgia
[4] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA
[5] Georgia Inst Technol, Sch Elect & Comp Engn, Sch Civil & Environm Engn, Atlanta, GA 30332 USA
关键词
Aerospace Control System; Applied Mathematics; Computing and Informatics; Lyapunov Stability Theory; Aerospace Sciences; Mathematical Optimization; Quadcopter; Drag Coefficient; Aircraft Flight Control System; Atmospheric Science; ROBUST STABILITY ANALYSIS; SUM; LMI;
D O I
10.2514/1.G006658
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
A method for constructing homogeneous polynomial Lyapunov functions is presented for linear time-varying or switched-linear systems and the class of nonlinear systems that can be represented as such. The method uses a simple recursion based on the Kronecker product to generate a hierarchy of related dynamical systems, whose first element is the system under study and the second element is the well-known Lyapunov differential equation. It is then proven that a quadratic Lyapunov function for the system at one level in the hierarchy, which can be found via semidefinite programming, is a homogeneous polynomial Lyapunov function for the system at the base level in the hierarchy. Searching for Lyapunov functions of the foregoing kind is equivalent to searching for homogeneous polynomial Lyapunov functions via the formulation of sum-of-squares programs. The quadratic perspective presented in this paper enables the easy development of procedures to compute bounds on pointwise-in-time system metrics, such as peak norms, system stability margins, and many other performance measures. The applications of the theory to analyzing an aircraft model, on the one hand, and an experimental aerospace vehicle, on the other hand, are presented. The theory can be comprehended with a first course on state-space control systems and an elementary knowledge of convex programming.
引用
收藏
页码:597 / 608
页数:12
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