Optimization and control of bilinear systems: Theory, by Panos M. Pardalos, Vitaliy A. Yatsenko
By Panos M. Pardalos, Vitaliy A. Yatsenko
Covers advancements in bilinear platforms thought
Focuses at the keep watch over of open actual methods functioning in a non-equilibrium mode
Emphasis is on 3 fundamental disciplines: smooth differential geometry, keep an eye on of dynamical structures, and optimization concept
Includes purposes to the fields of quantum and molecular computing, keep watch over of actual methods, biophysics, superconducting magnetism, and actual info science
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Extra resources for Optimization and control of bilinear systems: Theory, algorithms, and applications
A(i, j, M ) ⎡ ⎤ B0 (i, 0) B0 (i, 1) . . B0 (i, q) ⎢B1 (i, 0) B1 (i, 1) . . B1 (i, q)⎥ ⎢ ⎥ Bi = ⎢ .. ⎥ , ⎣ . ⎦ ⎡ Bq (i, 0) Bj (i, 1, k, 1) Bj (i, 2, k, 1) .. ⎢ ⎢ Bj (i, k) = ⎢ ⎣ Bj (i, Mk , k, 1) ...... Bq (i, q) Bj (i, 1, k, 2) . . ... ... Bj (i, 1, k, Mi ) Bj (i, 2, k, Mi ) .. ⎤ ⎥ ⎥ ⎥. 12) holds, where C = [I 0 . . 0], D = [0 ( ... i−1 j=0 0 I 0 ... 0]. 13) is true. This completes the proof of suﬃciency. Necessity. As the bilinear and nonlinear systems are dynamically equivalent, we have, for a control function v, p z(t) = h(x(t)) + Q(x(t))v(t) = Di vi (t) y(t).
7. 11) is said to have a ﬁnite-dimensional sensor orbit, if there exist integers Mi , i = 0, . . , q, such that for k = 1, . . , q, and all state trajectories x(t), t ∈ T , M0 −1 M0 L A(0, 0, i + 1)Li h(x(t)) h(x(t)) = i=0 q Mq −1 A(0, j, i + 1)Li Qj (x(t)), + j=1 i=0 M0 −1 Mk L A(k, 0, i + 1)Li h(x(t)) Qk (x(t)) = i=0 q Mq −1 A(k, j, i + 1)Li Qj (x(t)), + j=1 i=0 where A(i, j, k) are constant p × p matrices, and every column of (Li h(x(t)))x G(x(t)) and (Li Qj (x(t)))x G(x(t)), i = 0, . . , (Mj − 1), j = 1, .
5) is that Gl(m, R) is a Lie group and each Aj deﬁnes a right-invariant vector ﬁeld Aj X on this group, hence a member of the associated Lie algebra gl(m, R) of all m × m real matrices. This algebra is ﬁnite-dimensional over the ﬁeld R and the multiplication is deﬁned by the Lie bracket [Ai , Aj ] = Aj Ai − Ai Aj . This is a noncommutative and nonassociative operation that satisﬁes the skew-symmetry and Jacobi relations, [Ai , Aj ] = −[Aj , Ai ], and [Ai , [Aj , Ak ]] = [[Ai , Aj ], Ak ] + [Aj , [Ai , Ak ]].