Numerical analysis of time discretization of optimal control problems
Numerical analysis of time discretization of optimal control problems
Numerical analysis of time discretization of optimal control problems
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Theorem 1 (Poincaré). Let H(p,q) : R 2n → R be <strong>of</strong> class C 2 . Then the<br />
associated Hamiltonian flow is symplectic.<br />
Pro<strong>of</strong>. Denote the flow by ϕt. The amount Ψt := ∂ϕt(y0)/∂y0 is solution<br />
<strong>of</strong> the variational equation, and hence, skipping the arguments <strong>of</strong> H:<br />
d<br />
dt (Ψt·JΨt) = ˙ Ψt·JΨt+Ψt·J ˙ Ψt = ΨtD 2 HJ −⊤ JΨt+Ψt·JD 2 HΨt = 0,<br />
since J −⊤ J −1 is the identity matrix. Therefore Ψt·JΨt is invariant along<br />
the trajectory, and hence, equal to its initial value J, as was to be proved.<br />
<br />
Theorem 2 (Bochev-Scovel 1994). The partitioned Runge-Kutta schemes<br />
derived from the <strong>optimal</strong>ity system are symplectic.<br />
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