Mixed integer optimal control numerical solution method based on quantum annealing

Abstract

A mixed integer optimal control problem is one of the most important problems in the daily life and industrial production. In order to solve the computational complexity of solving an integer decisionvariable, the invention proposes a mixed integer optimal control numerical solution method based on quantum annealing. Firstly, a mixed integer optimal control model is established to describe a mixed integer optimal control problem. Then, the mixed integer optimal control model is converted into a mixed integer nonlinear programming model by using a control vector parameterization and fourth-order Runge-Kutta method. Thirdly, compared with the traditional intelligent optimization algorithm, a quantum annealing algorithm with a higher convergence speed and stronger global search ability is proposed, an integer decision variable is solved by using the quantum annealing algorithm, and an optimal floating point number control variable i solved by using a parallel differential evolution algorithm. Finally, an optimal mixed integer control decision is obtained by two-part interactive iterative optimization.

Description

[0001] 1. Technical field [0002] The technology involves using quantum annealing algorithm to solve mixed integer optimal control problems, specifically a numerical solution method for mixed integer optimal control based on quantum annealing. [0003] 2. Background technology [0004] The main problem of optimal control research is: under the condition of satisfying the dynamic constraints, to seek the optimal control strategy, so that the performance index of the problem takes the maximum or minimum value. It belongs to the category of optimization and has the same nature and theoretical basis as optimization. Such problems exist widely in various technical fields and social problems. Mixed integer optimal control problems refer to optimal control problems involving integer decision variables. This problem is a combinatorial optimization problem that includes both integer decision variables and floating-point control variables, and is widely used in smart cities, smart war...

AI Technical Summary

Problems solved by technology

However, due to the computational complexity of solving the optimal integer decision variables, the mixed integer optimal control problem has always been a difficult problem in the field of control and optimization.

Genetic algorithm, particle swarm algorithm, simulated annealing and other intelligent optimization algorithms are all suitable tools to deal with this problem, but these algorithms have more or less disadvantages such as poor local search ability or slow convergence speed

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