Jump to content

Rao Mease: Difference between revisions

From mintOC
Created page with "{{Dimensions |nd = 1 |nx = 1 |nw = 1 }} The '''Rao Mease problem''' is a very sensitive one-dimensional toy ODE model which is especially suited for multiple shooting solvers. It aims to minimize a quadratic Lagrange term. The optimal integer control functions shows bang bang behavior. == Mathematical formulation == <p> <math> \begin{array}{lll} \displaystyle \min_{x,w} && \int_0^{10} (x(t)^2 + w(..."
 
 
(10 intermediate revisions by the same user not shown)
Line 7: Line 7:
The '''Rao Mease problem''' is a very sensitive one-dimensional toy [[:Category:ODE model|ODE model]] which is especially suited for multiple shooting solvers. It aims to minimize a quadratic Lagrange term.
The '''Rao Mease problem''' is a very sensitive one-dimensional toy [[:Category:ODE model|ODE model]] which is especially suited for multiple shooting solvers. It aims to minimize a quadratic Lagrange term.


The optimal integer control functions shows [[:Category:Chattering|bang bang]] behavior.
The optimal control function exhibits a [[:Category:Sensitivity-seeking arcs|singular arc]].


== Mathematical formulation ==
== Mathematical formulation ==
Line 26: Line 26:
Here is one local solution to the above control problem.
Here is one local solution to the above control problem.


<gallery caption="Reference solution plots" widths="180px" heights="140px" perrow="1">
<gallery caption="Reference solution plots" widths="500px" heights="300px" perrow="1">
  Image:Toy OED.png| States and measurement control for different choices of <math>p</math>.
  Image:Rao_Mease.png| States and discretized control for a local optimum.
</gallery>
</gallery>


== Miscellaneous and Further Reading ==
== Miscellaneous and Further Reading ==
The Toy OED problem was introduced by Sebastian Sager in the paper <bib id="Sager2013" />, which contains further details.
The problem description and further references can be found in the PhD thesis of Michael Ernst Geiger [[#GeigerPhD|[1]]].


== References ==
== References ==
<biblist />
<span id="GeigerPhD">[1]</span> "Adaptive Multiple Shooting for Boundary Value Problems and Constrained Parabolic Optimization Problems" by M. E. Geiger  <br>
 


<!--List of all categories this page is part of. List characterization of solution behavior, model properties, ore presence of implementation details (e.g., AMPL for AMPL model) here -->
[[Category:MIOCP]]
[[Category:MIOCP]]
[[Category:Optimum Experimental Design]]
[[Category:Sensitivity-seeking arcs]]
[[Category:ODE model]]
[[Category:Bang bang]]

Latest revision as of 13:47, 28 November 2025

Rao Mease
State dimension: 1
Differential states: 1
Discrete control functions: 1


The Rao Mease problem is a very sensitive one-dimensional toy ODE model which is especially suited for multiple shooting solvers. It aims to minimize a quadratic Lagrange term.

The optimal control function exhibits a singular arc.

Mathematical formulation

minx,w010(x(t)2+w(t)2)dtsubject tox˙(t)=x(t)3+w(t),x(0)=1,x(10)=1.5

Reference Solutions

Here is one local solution to the above control problem.

Miscellaneous and Further Reading

The problem description and further references can be found in the PhD thesis of Michael Ernst Geiger [1].

References

[1] "Adaptive Multiple Shooting for Boundary Value Problems and Constrained Parabolic Optimization Problems" by M. E. Geiger