Domain of Attraction: Analysis and Control via SOS by Graziano Chesi

By Graziano Chesi

The balance of equilibrium issues performs a primary position in dynamical structures. For nonlinear dynamical structures, which symbolize nearly all of genuine crops, an research of balance calls for the characterization of the area of appeal (DA) of an equilibrium element, i.e., the set of preliminary stipulations from which the trajectory of the process converges to this type of element. it truly is famous that estimating the DA, or maybe extra trying to keep an eye on it, are very tough difficulties as a result advanced courting of this set with the version of the system.

The e-book additionally bargains a concise and easy description of the most beneficial properties of SOS programming that are utilized in study and educating. particularly, it introduces a number of periods of SOS polynomials and their characterization through LMIs and addresses average difficulties similar to institution of positivity or non-positivity of polynomials and matrix polynomials, deciding upon the minimal of rational features, and fixing platforms of polynomial equations, in circumstances of either unconstrained and limited variables. The recommendations provided during this e-book come in the MATLAB® toolbox SMRSOFT, which might be downloaded from http://www.eee.hku.hk/~chesi.

Domain of Attraction addresses the estimation and regulate of the DA of equilibrium issues utilizing the radical SOS programming scheme, i.e., optimization suggestions which have been lately built in line with polynomials which are sums of squares of polynomials (SOS polynomials) and that quantity to fixing convex optimization issues of linear matrix inequality (LMI) constraints, sometimes called semidefinite courses (SDPs). For the 1st time within the literature, a method of facing those matters is gifted in a unified framework for numerous instances looking on the character of the nonlinear structures thought of, together with the situations of polynomial platforms, doubtful polynomial platforms, and nonlinear (possibly doubtful) non-polynomial structures. The equipment proposed during this booklet are illustrated in numerous actual structures and simulated platforms with randomly selected buildings and/or coefficients such as chemical reactors, electrical circuits, mechanical units, and social versions.

The e-book additionally bargains a concise and straightforward description of the most good points of SOS programming that are utilized in examine and educating. specifically, it introduces a variety of periods of SOS polynomials and their characterization through LMIs and addresses general difficulties similar to institution of positivity or non-positivity of polynomials and matrix polynomials, picking out the minimal of rational capabilities, and fixing platforms of polynomial equations, in situations of either unconstrained and limited variables. The suggestions provided during this publication come in the MATLAB® toolbox SMRSOFT, that are downloaded from http://www.eee.hku.hk/~chesi.

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Extra info for Domain of Attraction: Analysis and Control via SOS Programming

Example text

F (x) is SOS if and only if λqua ( f ) ≥ 0. 4. f (x) is positive semidefinite if λqua ( f ) ≥ 0. 5. f (x) is positive definite if λqua ( f ) > 0. 6. λqua( f ) ≤ μqua ( f ). Proof. 2. The same results can be obtained for the class of homogeneous polynomials as explained hereafter. 15. 17 (SOS Index (continued)). Let f ∈ Pn be a homogeneous polynomial of even degree, and define f = COEhom ( f ) and F + L(α ) = CSMRhom ( f ). t. F + L(α ) − zI ≥ 0. 70) Then, λhom ( f ) is called SOS index of f (x) (for homogeneous polynomials).

Specifically, consider x ∈ Xhom and let i be such that xi = 0. 194) where y = (x1 , . . , xi−1 , xi+1 , . . , xn ) . 195) Indeed, the i-th entry of z(y) is 1, and z(y) is a function of n − 1 scalar variables, namely x1 , . . , xi−1 , xi+1 , . . , xn which are gathered into y. It follows that bhom (x, m) ∈ V and xi = 0 ⇐⇒ b pol (z(y), m) ∈ V . e. Xi = x = γ w(y) = (y1 , . . , yi−1 , 1, yi , . . , yn−1 ) . 199) x ∈ Xhom and xi = 0 ⇐⇒ x ∈ Xi . 200) It follows that Therefore, the sought set Xhom is finally found by repeating this procedure for all i = 1, .

F + L(α ) − zI ≥ 0. 70) Then, λhom ( f ) is called SOS index of f (x) (for homogeneous polynomials). 17. Clearly: 1. a homogeneous polynomial f (x) is positive semidefinite if and only if μhom ( f ) ≥ 0. 2. a homogeneous polynomial f (x) is positive definite if and only if μhom ( f ) > 0. 4. Let f ∈ Pn be a homogeneous polynomial of even degree. The following statements hold. 1. f (x) is SOS if and only if there exists α satisfying the LMI F + L(α ) ≥ 0 where F + L(α ) = CSMRhom ( f ). 2. The SOS index λhom( f ) exists (and, hence, is bounded).

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