Interval propagation

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

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

x 1 + x 2 = x 3 , {\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

[ x 3 ] := [ x 3 ] ( [ x 1 ] + [ x 2 ] ) {\displaystyle [x_{3}]:=[x_{3}]\cap ([x_{1}]+[x_{2}])}
[ x 1 ] := [ x 1 ] ( [ x 3 ] [ x 2 ] ) {\displaystyle [x_{1}]:=[x_{1}]\cap ([x_{3}]-[x_{2}])}
[ x 2 ] := [ x 2 ] ( [ x 3 ] [ x 1 ] ) {\displaystyle [x_{2}]:=[x_{2}]\cap ([x_{3}]-[x_{1}])}

For instance, if

x 1 [ , 5 ] , {\displaystyle x_{1}\in [-\infty ,5],}
x 2 [ , 4 ] , {\displaystyle x_{2}\in [-\infty ,4],}
x 3 [ 6 , ] {\displaystyle x_{3}\in [6,\infty ]}

the contractor performs the following calculus

x 3 = x 1 + x 2 x 3 [ 6 , ] ( [ , 5 ] + [ , 4 ] ) = [ 6 , ] [ , 9 ] = [ 6 , 9 ] . {\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].}
x 1 = x 3 x 2 x 1 [ , 5 ] ( [ 6 , ] [ , 4 ] ) = [ , 5 ] [ 2 , ] = [ 2 , 5 ] . {\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].}
x 2 = x 3 x 1 x 2 [ , 4 ] ( [ 6 , ] [ , 5 ] ) = [ , 4 ] [ 1 , ] = [ 1 , 4 ] . {\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].}
Figure 1: boxes before contraction
Figure 2: boxes after contraction

For other constraints, a specific algorithm for implementing the atomic contractor should be written. An illustration is the atomic contractor associated to the equation

x 2 = sin ( x 1 ) , {\displaystyle x_{2}=\sin(x_{1}),}

is provided by Figures 1 and 2.

Decomposition

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

x + sin ( x y ) 0 , {\displaystyle x+\sin(xy)\leq 0,}

could be decomposed into

a = x y {\displaystyle a=xy}
b = sin ( a ) {\displaystyle b=\sin(a)}
c = x + b . {\displaystyle c=x+b.}

The interval domains that should be associated to the new intermediate variables are

a [ , ] , {\displaystyle a\in [-\infty ,\infty ],}
b [ 1 , 1 ] , {\displaystyle b\in [-1,1],}
c [ , 0 ] . {\displaystyle c\in [-\infty ,0].}

Propagation

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

Consider the electronic circuit of Figure 3.

Figure 3: File:Electronic circuit to illustrate the interval propagation

Assume that from different measurements, we know that

E [ 23 V , 26 V ] {\displaystyle E\in [23V,26V]}
I [ 4 A , 8 A ] {\displaystyle I\in [4A,8A]}
U 1 [ 10 V , 11 V ] {\displaystyle U_{1}\in [10V,11V]}
U 2 [ 14 V , 17 V ] {\displaystyle U_{2}\in [14V,17V]}
P [ 124 W , 130 W ] {\displaystyle P\in [124W,130W]}
R 1 [ 0 Ω , ] {\displaystyle R_{1}\in [0\Omega ,\infty ]}
R 2 [ 0 Ω , ] . {\displaystyle R_{2}\in [0\Omega ,\infty ].}

From the circuit, we have the following equations

P = E I {\displaystyle P=EI}
U 1 = R 1 I {\displaystyle U_{1}=R_{1}I}
U 2 = R 2 I {\displaystyle U_{2}=R_{2}I}
E = U 1 + U 2 . {\displaystyle E=U_{1}+U_{2}.}

After performing the interval propagation, we get

E [ 24 V , 26 V ] {\displaystyle E\in [24V,26V]}
I [ 4.769 A , 5.417 A ] {\displaystyle I\in [4.769A,5.417A]}
U 1 [ 10 V , 11 V ] {\displaystyle U_{1}\in [10V,11V]}
U 2 [ 14 V , 16 V ] {\displaystyle U_{2}\in [14V,16V]}
P [ 124 W , 130 W ] {\displaystyle P\in [124W,130W]}
R 1 [ 1.846 Ω , 2.307 Ω ] {\displaystyle R_{1}\in [1.846\Omega ,2.307\Omega ]}
R 2 [ 2.584 Ω , 3.355 Ω ] . {\displaystyle R_{2}\in [2.584\Omega ,3.355\Omega ].}

References

  1. ^ 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).
  2. ^ Cleary, J.L. (1987). Logical arithmetic. Future Computing Systems.
  3. ^ Jaulin, L. (2006). Localization of an underwater robot using interval constraints propagation (PDF). In Proceedings of CP 2006.