Math 2.0

Calculus of variations and optimal control; optimization Definition

Relaxed control

Builds on Admissible controlProbability measureCompact setControl systemYoung measureFilippov's existence theorem

Definition

Let UU be a nonempty compact set in ℝm\R^m, and let 𝒫(U)\mathcal{P}(U) be the set of Borel probability measures on UU. Let T>0T > 0. A relaxed control on [0,T][0, T] is a family (μt)t∈[0,T](\mu_t)_{t \in [0, T]} with μt∈𝒫(U)\mu_t \in \mathcal{P}(U) for every tt. It must be measurable in this sense: for every continuous function h ⁣:U→ℝh \colon U \to \R, the map t↦∫Uh dμtt \mapsto \int_U h \, d\mu_t is Lebesgue measurable on [0,T][0, T]. For a control system x′=f(t,x,u)x' = f(t, x, u) with ff continuous, the trajectory of the relaxed control (μt)(\mu_t) solves the relaxed equation x′(t)=∫Uf(t,x(t),v) dμt(v).x'(t) = \int_U f(t, x(t), v) \, d\mu_t(v).

Remarks

Every ordinary admissible control u ⁣:[0,T]→Uu \colon [0, T] \to U gives the relaxed control μt=δu(t)\mu_t = \delta_{u(t)}, the Dirac measure at u(t)u(t). Its relaxed equation is x′=f(t,x,u(t))x' = f(t, x, u(t)), the original one. Example: U={−1,1}U = \set{-1, 1} and μt=12δ−1+12δ1\mu_t = \frac12 \delta_{-1} + \frac12 \delta_1 for all tt. It is a relaxed control, since ∫Uh dμt=12(h(−1)+h(1))\int_U h \, d\mu_t = \frac12 (h(-1) + h(1)) is constant in tt. For f(t,x,u)=uf(t, x, u) = u its trajectory has x′=0x' = 0, a velocity that no ordinary control with values in {−1,1}\set{-1, 1} gives. Non-example: μt=δ−1+δ1\mu_t = \delta_{-1} + \delta_1 is not a relaxed control, since μt(U)=2\mu_t(U) = 2, so μt\mu_t is not a probability measure. The velocities of relaxed controls fill the convex hull of f(t,x,U)f(t, x, U), so the convexity hypothesis of Filippov's existence theorem holds for the relaxed problem. A relaxed control is a Young measure on [0,T][0, T] with values in UU.

Reading path

To understand this page from the ground up, read these 14 pages in order. The foundations come first.

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Each page uses the pages above it. The colour of the bar on a box shows how strong the evidence is, and the box also gives it as text. The list has the same pages.
  • no evidence level
  1. Absolute continuity concept
  2. Admissible control concept
  3. Compact set concept
  4. Control system concept
  5. Convex set concept
  6. Differential inclusion concept
  7. Functional concept
  8. Optimal control concept
  9. Probability measure concept
  10. Young measure concept
  11. Pontryagin's maximum principle statement
  12. Mayer and Lagrange problems problem
  13. Filippov's existence theorem statement
  14. Relaxed control definition

Further reading

  1. Web https://en.wikipedia.org/wiki/Optimal_control
About this page
TagSH95P4SEWT
URIm2://SH95P4SEWT
Kinddefinition
WritingW0 stub
MSC49J15, 49J45, 93C15
DefinesRelaxed control
UsesAdmissible control, Probability measure, Compact set, Control system, Young measure, Filippov's existence theorem

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