6533b7d3fe1ef96bd1260975

RESEARCH PRODUCT

Optimal Impulse Control Problems and Linear Programming

Dario Bauso

subject

PolynomialMathematical optimizationUnimodular matrixComputational complexity theoryLinear programmingbusiness.industryImpulse control hybrid systems optimal controlLocal search (optimization)Relaxation (approximation)Optimal controlbusinessTime complexityMathematics

description

Optimal impulse control problems are, in general, difficult to solve. A current research goal is to isolate those problems that lead to tractable solutions. In this paper, we identify a special class of optimal impulse control problems which are easy to solve. Easy to solve means that solution algorithms are polynomial in time and therefore suitable to the on-line implementation in real-time problems. We do this by using a paradigm borrowed from the Operations Research field. As main result, we present a solution algorithm that converges to the exact solution in polynomial time. Our approach consists in approximating the optimal impulse control problem via a binary linear programming problem with a totally unimodular constraint matrix. Hence, solving the binary linear programming problem is equivalent to solving its linear relaxation. It turns out that any solution of the linear relaxation is a feasible solution for the optimal impulse control problem. Then, given the feasible solution, obtained solving the linear relaxation, we find the optimal solution via local search.

10.1109/cdc.2009.5399855http://hdl.handle.net/10447/77868