Math 2.0

Calculus of variations and optimal control; optimization Second variation and sufficient conditions Theorem

Weierstrass–Erdmann corner conditions

Builds on Integral functional with a Lagrangian densityWeak and strong extremumEuler–Lagrange equation

Statement

Let a<ba < b and let L ⁣:[a,b]×ℝn×ℝn→ℝL \colon [a, b] \times \R^n \times \R^n \to \R, written L(x,y,p)L(x, y, p), be of class C1C^1. Let J(y)=∫abL(x,y,y′) dxJ(y) = \int_a^b L(x, y, y') \, dx on piecewise C1C^1 functions y ⁣:[a,b]→ℝny \colon [a, b] \to \R^n with fixed values at aa and bb. Let y0y_0 be a piecewise C1C^1 strong local minimiser of JJ in this class. Let c∈(a,b)c \in (a, b) be a corner of y0y_0, with one-sided derivatives p−=y0′(c−)p_- = y_0'(c^-) and p+=y0′(c+)p_+ = y_0'(c^+). Then Lp(c,y0(c),p−)=Lp(c,y0(c),p+),L_p(c, y_0(c), p_-) = L_p(c, y_0(c), p_+), L(c,y0(c),p−)−p−⋅Lp(c,y0(c),p−)=L(c,y0(c),p+)−p+⋅Lp(c,y0(c),p+).L(c, y_0(c), p_-) - p_- \cdot L_p(c, y_0(c), p_-) = L(c, y_0(c), p_+) - p_+ \cdot L_p(c, y_0(c), p_+).

Remarks

The first condition comes from variations y0+εhy_0 + \varepsilon h with hh supported near cc. The du Bois-Reymond form of the Euler–Lagrange equation says that Lp(x,y0,y0′)L_p(x, y_0, y_0') equals a continuous function of xx, so it has no jump at cc. The second condition comes from moving the corner point sideways, which is a variation of the independent variable xx.

Example: let J(y)=∫02(y′2−1)2 dxJ(y) = \int_0^2 (y'^2 - 1)^2 \, dx with y(0)=y(2)=0y(0) = y(2) = 0. The zigzag y0(x)=min⁡(x,2−x)y_0(x) = \min(x, 2 - x) has J(y0)=0J(y_0) = 0, so it is a minimiser, with a corner at 11 where p−=1p_- = 1 and p+=−1p_+ = -1. Here Lp=4p(p2−1)L_p = 4p(p^2 - 1) and L−pLp=(p2−1)2−4p2(p2−1)L - p L_p = (p^2 - 1)^2 - 4p^2(p^2 - 1), and both vanish at p=±1p = \pm 1, as the theorem requires.

If Lpp>0L_{pp} > 0 everywhere, the map p↦Lp(x,y,p)p \mapsto L_p(x, y, p) is injective when n=1n = 1, and the first condition forces p−=p+p_- = p_+. So for such Lagrangians minimisers have no corners.

Going deeper

For a student

The Euler–Lagrange equation holds on each smooth piece of a broken extremal, but it says nothing about how the pieces join. The Weierstrass–Erdmann conditions supply the missing junction conditions, two of them, which match the freedom in the location and the slopes at a corner. In Hamiltonian terms they say that the momentum LpL_p and the Hamiltonian p⋅Lp−Lp \cdot L_p - L are continuous along the extremal. They explain why problems with Lagrangians that are not convex in pp often have broken minimisers.

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  1. Euler–Lagrange equation concept
  2. Integral functional with a Lagrangian density concept
  3. Weak and strong extremum concept
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Further reading

  1. Web https://en.wikipedia.org/wiki/Weierstrass%E2%80%93Erdmann_condition
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