Download Linear Port-Hamiltonian Systems on Infinite-dimensional by Birgit Jacob, Hans J. Zwart PDF

By Birgit Jacob, Hans J. Zwart

This e-book offers a self-contained creation to the speculation of infinite-dimensional structures conception and its functions to port-Hamiltonian structures. The textbook begins with user-friendly identified effects, then progresses easily to complicated themes in present research.

Many actual platforms might be formulated utilizing a Hamiltonian framework, resulting in versions defined by means of traditional or partial differential equations. For the aim of regulate and for the interconnection of 2 or extra Hamiltonian structures it's necessary to take into consideration this interplay with the surroundings. This ebook is the 1st textbook on infinite-dimensional port-Hamiltonian platforms. An summary sensible analytical procedure is mixed with the actual method of Hamiltonian platforms. This mixed technique ends up in simply verifiable stipulations for well-posedness and stability.

The booklet is available to graduate engineers and mathematicians with a minimum historical past in sensible research. additionally, the speculation is illustrated by means of many worked-out examples.

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Extra info for Linear Port-Hamiltonian Systems on Infinite-dimensional Spaces

Example text

S ≥ 0. 5) Let t > 0 be arbitrary. 5) that t x∗ Wt = x∗ eAs BB ∗ eA ∗ s ds = 0, 0 and therefore x ∈ (ran Wt )⊥ . Conversely, let x ∈ (ran Wt )⊥ for some t > 0. This implies t 0 = x∗ Wt x = ∗ B ∗ eA s x 2 ds. 0 ∗ As the function s → B ∗ eA s x 2 is continuous and non-negative, we obtain ∗ B ∗ eA s x = 0 for every s ∈ [0, t]. In particular, x∗ B = 0. Moreover, we obtain 0= ∗ dk (B ∗ eA s x) k ds = B ∗ (A∗ )k x, k ∈ N. s=0 This implies x∗ Ak B = 0 for every k ∈ N, and thus in particular x ∈ (ran R(A, B))⊥ .

N − 2, 1, j = n − 1. 16) Next we show that the vectors vn∗ , vn∗ A, . . , vn∗ An−1 are linearly independent. Therefore we assume that there exist scalars α1 , . . , αn such that n αi vn∗ Ai−1 = 0. 17) i=1 Multiplying this equation from the right by b yields n αi vn∗ Ai−1 b = 0. 16) implies αn = 0. 16), then implies αn−1 = 0. 17) sequently by b, Ab, A2 b, . . 2. 16), implies α1 = · · · = αn = 0, that is, the vectors vn∗ , vn∗ A, . . , vn∗ An−1 are linearly independent. 18) ⎥ ∈ Kn×n .. ⎣ ⎦ .

Next we assume that Σ(A, B) is stabilizable. We now define Xs by the span of all generalized eigenspaces corresponding to eigenvalues of A with negative real part and Xu by the span of all generalized eigenspaces corresponding to eigenvalues of A with non-negative real part. Thus, Xs and Xu are A-invariant, Xs ∩Xu = {0} and Xs ⊕ Xu = Cn . If we choose our basis of Cn accordingly, it is easy to see that the system Σ(A, B) is similar to a system of the form Σ As 0 0 Bs , Au Bu . By definition of the space Xs , the matrix As is a Hurwitz matrix.

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