Algebraic Methods for Nonlinear Control Systems by Giuseppe Conte, Claude H. Moog, Anna Maria Perdon

By Giuseppe Conte, Claude H. Moog, Anna Maria Perdon

This can be a self-contained advent to algebraic keep watch over for nonlinear structures appropriate for researchers and graduate scholars. it's the first ebook facing the linear-algebraic method of nonlinear keep an eye on platforms in this kind of specified and large model. It presents a complementary method of the extra conventional differential geometry and offers extra simply with a number of very important features of nonlinear platforms.

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Extra resources for Algebraic Methods for Nonlinear Control Systems (Communications and Control Engineering)

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6) for any k ≥ 1. 6, this is not true for ω = dϕ and k = ν + 1. This ends the proof of statement (i). 7) for any k ≥ 1. 6. The notion of autonomous element can be defined also in the context of nonexact forms. 10. 1) if there exists an integer ν and meromorphic function coefficients αi in K, for i = 1, . . , ν, so that α0 ω + . . 11. 12. A one form ω in X is an autonomous element if and only if it has an infinite relative degree. Proof. Necessity: Assume that ω in X has an infinite relative degree.

8) with internal variables. 11) can be said to be a generalized realization; the adjective “generalized” accounts for the presence of derivatives of u. According to this, the variable x can be interpreted as a generalized state variable. In addition, note that the application of the implicit function theorem, beside being nonconstructive, does not guarantee that ϕ is a meromorphic function. 4. Consider the input-output equation y˙ 2 = y + u. The above procedure yields the implicit state equations x˙ 2 = x + u or, locally, one of the following explicit realizations, depending on whether y˙ > 0 or y˙ < 0.

Dyi1 , . . , dyi1 i1 } be a basis for ( ) ∗ Xi+1,1 := Xi + Ds+2 ∩ spanK {dyi1 , ≥ 0} where ri1 = dimXi+1,1 − dimXi . ( ) ∗ ∩ spanK {dyij , ≥ 0} = 0 for j = 2, . . , 2i−1 , then stop! • If Ds+2 i−1 • For j = 2, . . , 2 , let 36 2 Modeling (r −1) {dy, . . , dy (r−1) ; . . ; dyij , . . , dyij ij } be a basis for ( ) ∗ Xi+1,j := Xi+1,j−1 + Ds+2 ∩ spanK {dyij , ≥ 0} where rij = dimXi+1,j − dimXi+1,j−1 . Set Xi+1 = (r ) • If ∀ ≥ rij , dyij ij ∈ Xi+1 , set sij = −1. Xi+1,j ( ) If ∃ ≥ rij , dyij ∈ Xi+1 , then define sij as the smallest integer such that, abusing the notation, one has locally (r +sij ) yij ij (r +sij ) = yij ij (σ) (y (λ) , yij , u, .

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