Interval propagation
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In numerical mathematics, interval propagation or interval constraint propagation is the problem of contracting interval domains associated to variables of R without removing any value that is consistent with a set of constraints (i.e., equations or inequalities). It can be used to propagate uncertainties in the situation where errors are represented by intervals.[1] Interval propagation considers an estimation problem as a constraint satisfaction problem.
Atomic contractors
[edit ]A contractor associated to an equation involving the variables x1,...,xn is an operator which contracts the intervals [x1],..., [xn] (that are supposed to enclose the xi's) without removing any value for the variables that is consistent with the equation.
A contractor is said to be atomic if it is not built as a composition of other contractors. The main theory that is used to build atomic contractors are based on interval analysis.
Example. Consider for instance the equation
- {\displaystyle x_{1}+x_{2}=x_{3},}
which involves the three variables x1,x2 and x3.
The associated contractor is given by the following statements
- {\displaystyle [x_{3}]:=[x_{3}]\cap ([x_{1}]+[x_{2}])}
- {\displaystyle [x_{1}]:=[x_{1}]\cap ([x_{3}]-[x_{2}])}
- {\displaystyle [x_{2}]:=[x_{2}]\cap ([x_{3}]-[x_{1}])}
For instance, if
- {\displaystyle x_{1}\in [-\infty ,5],}
- {\displaystyle x_{2}\in [-\infty ,4],}
- {\displaystyle x_{3}\in [6,\infty ]}
the contractor performs the following calculus
- {\displaystyle x_{3}=x_{1}+x_{2}\Rightarrow x_{3}\in [6,\infty ]\cap ([-\infty ,5]+[-\infty ,4])=[6,\infty ]\cap [-\infty ,9]=[6,9].}
- {\displaystyle x_{1}=x_{3}-x_{2}\Rightarrow x_{1}\in [-\infty ,5]\cap ([6,\infty ]-[-\infty ,4])=[-\infty ,5]\cap [2,\infty ]=[2,5].}
- {\displaystyle x_{2}=x_{3}-x_{1}\Rightarrow x_{2}\in [-\infty ,4]\cap ([6,\infty ]-[-\infty ,5])=[-\infty ,4]\cap [1,\infty ]=[1,4].}
For other constraints, a specific algorithm for implementing the atomic contractor should be written. An illustration is the atomic contractor associated to the equation
- {\displaystyle x_{2}=\sin(x_{1}),}
is provided by Figures 1 and 2.
Decomposition
[edit ]For more complex constraints, a decomposition into atomic constraints (i.e., constraints for which an atomic contractor exists) should be performed. Consider for instance the constraint
- {\displaystyle x+\sin(xy)\leq 0,}
could be decomposed into
- {\displaystyle a=xy}
- {\displaystyle b=\sin(a)}
- {\displaystyle c=x+b.}
The interval domains that should be associated to the new intermediate variables are
- {\displaystyle a\in [-\infty ,\infty ],}
- {\displaystyle b\in [-1,1],}
- {\displaystyle c\in [-\infty ,0].}
Propagation
[edit ]The principle of the interval propagation is to call all available atomic contractors until no more contraction could be observed. [2] As a result of the Knaster-Tarski theorem, the procedure always converges to intervals which enclose all feasible values for the variables. A formalization of the interval propagation can be made thanks to the contractor algebra. Interval propagation converges quickly to the result and can deal with problems involving several hundred of variables. [3]
Example
[edit ]Consider the electronic circuit of Figure 3.
Assume that from different measurements, we know that
- {\displaystyle E\in [23V,26V]}
- {\displaystyle I\in [4A,8A]}
- {\displaystyle U_{1}\in [10V,11V]}
- {\displaystyle U_{2}\in [14V,17V]}
- {\displaystyle P\in [124W,130W]}
- {\displaystyle R_{1}\in [0\Omega ,\infty ]}
- {\displaystyle R_{2}\in [0\Omega ,\infty ].}
From the circuit, we have the following equations
- {\displaystyle P=EI}
- {\displaystyle U_{1}=R_{1}I}
- {\displaystyle U_{2}=R_{2}I}
- {\displaystyle E=U_{1}+U_{2}.}
After performing the interval propagation, we get
- {\displaystyle E\in [24V,26V]}
- {\displaystyle I\in [4.769A,5.417A]}
- {\displaystyle U_{1}\in [10V,11V]}
- {\displaystyle U_{2}\in [14V,16V]}
- {\displaystyle P\in [124W,130W]}
- {\displaystyle R_{1}\in [1.846\Omega ,2.307\Omega ]}
- {\displaystyle R_{2}\in [2.584\Omega ,3.355\Omega ].}
References
[edit ]- ^ Jaulin, L.; Braems, I.; Walter, E. (2002). Interval methods for nonlinear identification and robust control (PDF). In Proceedings of the 41st IEEE Conference on Decision and Control (CDC).
- ^ Cleary, J.L. (1987). Logical arithmetic. Future Computing Systems.
- ^ Jaulin, L. (2006). Localization of an underwater robot using interval constraints propagation (PDF). In Proceedings of CP 2006.