Calculus of variations and optimal control; optimization Definition
Relaxed control
Builds on Admissible controlProbability measureCompact setControl systemYoung measureFilippov's existence theorem
Definition
Let be a nonempty compact set in , and let be the set of Borel probability measures on . Let . A relaxed control on is a family with for every . It must be measurable in this sense: for every continuous function , the map is Lebesgue measurable on . For a control system with continuous, the trajectory of the relaxed control solves the relaxed equation
Remarks
Every ordinary admissible control gives the relaxed control , the Dirac measure at . Its relaxed equation is , the original one. Example: and for all . It is a relaxed control, since is constant in . For its trajectory has , a velocity that no ordinary control with values in gives. Non-example: is not a relaxed control, since , so is not a probability measure. The velocities of relaxed controls fill the convex hull of , so the convexity hypothesis of Filippov's existence theorem holds for the relaxed problem. A relaxed control is a Young measure on with values in .
Reading path
To understand this page from the ground up, read these 14 pages in order. The foundations come first.
Show the path as a graph
- no evidence level
- Absolute continuity concept
- Admissible control concept
- Compact set concept
- Control system concept
- Convex set concept
- Differential inclusion concept
- Functional concept
- Optimal control concept
- Probability measure concept
- Young measure concept
- Pontryagin's maximum principle statement
- Mayer and Lagrange problems problem
- Filippov's existence theorem statement
- Relaxed control definition
Further reading
About this page
| Tag | SH95P4SEWT |
|---|---|
| URI | m2://SH95P4SEWT |
| Kind | definition |
| Writing | W0 stub |
| MSC | 49J15, 49J45, 93C15 |
| Defines | Relaxed control |
| Uses | Admissible control, Probability measure, Compact set, Control system, Young measure, Filippov's existence theorem |
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