Math 2.0

Calculus of variations and optimal control; optimization Definition

Carathéodory's royal road

Builds on Calculus of variationsHamilton–Jacobi equation

Definition

Let a<ba < b, let G⊆ℝ×ℝnG \subseteq \R \times \R^n be open, and let L ⁣:G×ℝn→ℝL \colon G \times \R^n \to \R be continuous, written L(t,x,v)L(t, x, v). For a C1C^1 curve y ⁣:[a,b]→ℝny \colon [a, b] \to \R^n with graph in GG, let J(y)=∫abL(t,y(t),y′(t)) dtJ(y) = \int_a^b L(t, y(t), y'(t)) \, dt, a functional of the calculus of variations. Let xˉ\bar x be a C1C^1 curve with graph in GG. Carathéodory's royal road is the following method to show that xˉ\bar x minimises JJ among such curves with the same endpoints. One looks for a C1C^1 function S ⁣:G→ℝS \colon G \to \R and a continuous map ψ ⁣:G→ℝn\psi \colon G \to \R^n such that:

  1. L(t,x,v)−St(t,x)−∇xS(t,x)⋅v≥0L(t, x, v) - S_t(t, x) - \nabla_x S(t, x) \cdot v \ge 0 for all (t,x)∈G(t, x) \in G and v∈ℝnv \in \R^n;
  2. L(t,x,ψ(t,x))−St(t,x)−∇xS(t,x)⋅ψ(t,x)=0L(t, x, \psi(t, x)) - S_t(t, x) - \nabla_x S(t, x) \cdot \psi(t, x) = 0 for all (t,x)∈G(t, x) \in G;
  3. xˉ′(t)=ψ(t,xˉ(t))\bar x'(t) = \psi(t, \bar x(t)) for all t∈[a,b]t \in [a, b].

The function L∗(t,x,v)=L(t,x,v)−St(t,x)−∇xS(t,x)⋅vL^*(t, x, v) = L(t, x, v) - S_t(t, x) - \nabla_x S(t, x) \cdot v is the equivalent Lagrangian of LL with respect to SS.

Remarks

The method works because of this identity, valid for every admissible curve yy: J(y)=∫abL∗(t,y(t),y′(t)) dt+S(b,y(b))−S(a,y(a)).J(y) = \int_a^b L^*(t, y(t), y'(t)) \, dt + S(b, y(b)) - S(a, y(a)). The boundary terms depend only on the endpoints. By clauses 1 to 3, the integral of L∗L^* is ≥0\ge 0 for every yy and =0= 0 for xˉ\bar x, so J(y)≥J(xˉ)J(y) \ge J(\bar x).

Clauses 1 and 2 say that min⁡vL∗(t,x,v)=0\min_v L^*(t, x, v) = 0, with the minimum at v=ψ(t,x)v = \psi(t, x). With H(t,x,p)=sup⁡v(p⋅v−L(t,x,v))H(t, x, p) = \sup_v (p \cdot v - L(t, x, v)), this means St+H(t,x,∇xS)=0S_t + H(t, x, \nabla_x S) = 0, the Hamilton–Jacobi equation.

Example: n=1n = 1, G=ℝ2G = \R^2, L=12v2L = \frac{1}{2} v^2, and xˉ(t)=t\bar x(t) = t on [0,1][0, 1]. Take S(t,x)=x−t/2S(t, x) = x - t/2 and ψ=1\psi = 1. Then L∗=12v2+12−v=12(v−1)2L^* = \frac{1}{2} v^2 + \frac{1}{2} - v = \frac{1}{2} (v - 1)^2, which is ≥0\ge 0 and vanishes at v=1v = 1, and xˉ′=1\bar x' = 1. So xˉ(t)=t\bar x(t) = t minimises ∫0112y′2 dt\int_0^1 \frac{1}{2} y'^2 \, dt among C1C^1 curves from (0,0)(0, 0) to (1,1)(1, 1).

Non-example: in the same problem, S=0S = 0 with ψ=1\psi = 1 fails clause 2, since L(t,x,1)=12≠0L(t, x, 1) = \frac{1}{2} \ne 0.

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Further reading

  1. Web https://en.wikipedia.org/wiki/Calculus_of_variations
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