Abstract
The paper provides second-order sufficient conditions for the strong local optimality of bang–bang–singular extremals in a Mayer problem with general end point constraints. The sufficient conditions are expressed as a strengthening of the necessary ones plus the coerciveness of a suitable quadratic form related to a sub-problem of the given one. The sufficiency of the given conditions is proven via Hamiltonian methods.
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The first author acknowledges the partial support given by INDAM-GNAMPA.
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Communicated by Aram Arutyunov.
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Appendices
Appendices
Computation of the Extended Second Variation
Problem (15) can be written as
We can allow for the controls \(\delta \upsilon _0\), \(\delta \upsilon \) to be in \(L^2 := L^2([0, T], {\mathbb {R}}) \) since equation (41) is linear with respect to the controls. Defining
we get
We aim at computing the second-order approximation \(C^{\prime \prime }\) of \(\varDelta C\).
By the properties of \(\gamma \), the constraint on \(\delta \upsilon _0\), and PMP it is not difficult to see that
Thus, the first-order approximation is null and the second-order approximation is intrinsically well defined. Obviously,
Denote as \({\mathcal {L}}^{\prime \prime }_t\) the second-order derivative of \({\mathcal {L}}_t\) at \(({\widehat{x}}_T, 0,0)\) and let \(\delta \eta \) be the linearization of \(\eta \), i.e. \(\delta \eta \) solves the problem
Hence
For the sake of computations, let us define
Let \(\varepsilon _0 := \displaystyle \int _0^{{\widehat{\tau }}_{1}}\delta \upsilon _0(s) {\text {d}}s\). Then
In particular
Define \(w(t) := \displaystyle \int _{{\widehat{\tau }}_{2}}^t - \delta \upsilon (s) {\text {d}}s\), \(\varepsilon _1 := w(T)\) and let \(\zeta :[{\widehat{\tau }}_{2}, T] \rightarrow {{\mathbb {R}}}^n\) solve the Cauchy problem
By (42), \(\zeta (T) = {\delta x}+ \varepsilon _1 f_{\mathrm{d}}({\widehat{x}}_T)\). Moreover, applying an intrinsic version of Goh transformation as in [9] we obtain
Thus
subject to
Notice that \(\delta \upsilon _0\) appears only through \(\varepsilon _0\), while the immersion
is continuous and dense. Thus we can extend \(C^{\prime \prime }\) to variations \( {\delta e}{:=} \left( {\delta x}, \delta y, \varepsilon _0, \varepsilon _1, w \right) \in {\mathcal {W}}_\mathrm{ext}\) as defined in Sect. 5, and the extension coincides with \(J_\mathrm{ext}\).
Splitting of the Second Variation
Lemma B.1
Assume \(f_{\mathrm{d}}({\widehat{x}}_T) \in T_{{\widehat{x}}_T}N_T\). Then the coerciveness of \(J_{\mathrm{ext}}\) on \({\mathcal {W}}_{\mathrm{ext}}\) splits into \( L^2_{f_{\mathrm{d}}}{\beta } \left( {{\widehat{x}}_T}\right) > 0 \) plus the coerciveness of J on \({\mathcal {W}}\).
Proof
We decompose \({\delta x}\in T_{{\widehat{x}}_T}N_T\) as \({\delta x}= \delta z+ rf_{\mathrm{d}}({\widehat{x}}_T)\), \(\delta z\in T_{{\widehat{x}}_T}\widetilde{N}_T\), where \(\widetilde{N}_T\) is the manifold defined in Sect. 5.1. We can compute
The above computation shows that the real variable r is decoupled and \(\delta z+ (r + \varepsilon _1) f_{\mathrm{d}}({\widehat{x}}_T)\) is a generic vector \({\delta x}\in T_{{\widehat{x}}_T}N_T\). This proves the claim. \(\square \)
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Poggiolini, L., Stefani, G. Strong Local Optimality for a Bang–Bang–Singular Extremal: General Constraints. J Optim Theory Appl 186, 24–49 (2020). https://doi.org/10.1007/s10957-020-01700-2
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DOI: https://doi.org/10.1007/s10957-020-01700-2