Covector mapping principle

Principle in control theory From Wikipedia, the free encyclopedia

The covector mapping principle is a special case of Riesz' representation theorem, which is a fundamental theorem in functional analysis. The name was coined by Ross and coauthors,[1][2][3][4][5][6] It provides conditions under which dualization can be commuted with discretization in the case of computational optimal control.

Description

An application of Pontryagin's minimum principle to Problem , a given optimal control problem generates a boundary value problem. According to Ross, this boundary value problem is a Pontryagin lift and is represented as Problem .

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Illustration of the Covector Mapping Principle (adapted from Ross and Fahroo.[7]

Now suppose one discretizes Problem . This generates Problem where represents the number of discrete points. For convergence, it is necessary to prove that as

In the 1960s Kalman and others[8] showed that solving Problem is extremely difficult. This difficulty, known as the curse of complexity,[9] is complementary to the curse of dimensionality.

In a series of papers starting in the late 1990s, Ross and Fahroo showed that one could arrive at a solution to Problem (and hence Problem ) more easily by discretizing first (Problem ) and dualizing afterwards (Problem ). The sequence of operations must be done carefully to ensure consistency and convergence. The covector mapping principle asserts that a covector mapping theorem can be discovered to map the solutions of Problem to Problem thus completing the circuit.

See also

References

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