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Ivancevic_Applied-Diff-Geom

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<strong>Applied</strong> Manifold <strong>Geom</strong>etry 231with ξ 1 , ξ 2 being two of the three basis elements for the tangent Lie algebrase(2) given by⎡ ⎤0 −1 0ξ 1 = ⎣ 1 0 0 ⎦ ,⎡ ⎤0 0 1ξ 2 = ⎣ 1 0 0 ⎦ ,⎡ ⎤0 0 0ξ 3 = ⎣ 1 0 1 ⎦ .0 0 00 0 00 0 0If p 1 (resp. p 2 ) is a cotangent vector–field to SE(2) at g 1 (resp. g 2 ), belongingto the cotangent (dual) Lie algebra se(2) ∗ , we can define the momentumfunctions for both vehicles:P 1 1 = < p 1 , g 1 ξ 1 >, P 2 1 =< p 1 , g 1 ξ 2 >, P 3 1 =< p 1 , g 1 ξ 3 >,P 1 2 = < p 2 , g 2 ξ 1 >, P 2 2 =< p 2 , g 2 ξ 2 >, P 3 2 =< p 2 , g 2 ξ 3 >,which can be compactly written asP j i =< p i, g i ξ j > .Defining p = (p 1 , p 2 ) ∈ se(2) ∗ × se(2) ∗ , the optimal cost for the two-player,zero-sum dynamical game is given byJ ∗ (g, t) = maxminu∈U d∈DThe Hamiltonian H(g, p, u, d) is given byJ(g, u(·), d(·), t) = maxu∈U mind∈D l(g(0)).H(g, p, u, d) = P 1 1 ω 1 + P 2 1 v 1 + P 1 2 ω 1 + P 2 2 v 1for control and disturbance inputs (ω 1 , v 1 ) ∈ U and (ω 2 , v 2 ) ∈ D as definedabove. It follows that the optimal Hamiltonian H ∗ (g, p), defined on thecotangent bundle T ∗ SE(2), is given byH ∗ (g, p) = P 1 1ω max1 + ω min1+ P 1 ω max22− |P1 1 | ωmax 2 − ω min2+ P12 2+ |P1 2 | vmax 1 − v1min− |P1 2 | vmax2and the saddle solution (u ∗ , d ∗ ) is given byu ∗ = arg maxminu∈U d∈DH(g, p, u, d), d∗2 + ω min22v1 max + v1min+ P22 22 − v2min2= arg minmaxd∈D u∈U+ |P1 1 | ωmax 1 − ω min12v2 max + v2min2H(g, p, u, d). (3.62)Note that H(g, p, u, d) and H ∗ (g, p) do not depend on the state g andcostate p directly, rather through the momentum functions P j 1 , P j 2 . Thisis because the dynamics are determined by left–invariant vector–fields on

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