Perturbation methods in optimal control problems

Buldaev, A. S.

doi:10.1016/j.ecolmodel.2008.03.030

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Cited by 2 publications

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“…To solve (14), which is an unconstrained optimization problem, we can use any optimization algorithms such as steepest descent, Newton, or Quasi Newton methods as well as the heuristic algorithms such as GA (genetic algorithm) or particle swarm optimization algorithm (PSO). After terminating the optimization step, we can replace the optimal values of the weights ψ into the Eq.…”

Section: Definition 1 ([26])mentioning

confidence: 99%

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Approximating the Solution of Optimal Control Problems by Fuzzy Systems

Pakdaman

Effati

2015

Neural Process Lett

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In this paper, the ability of fuzzy systems is used to estimate the solution of crisp optimal control problems. To solve an optimal control problem, first the well-known EulerLagrange conditions are obtained and then, the solution of these conditions is approximated by defining a trial solution based on fuzzy systems. The parameters of fuzzy systems are adjusted by an optimization algorithm. Numerical examples and comparisons with exact solutions reveal the capability and accuracy of proposed method.

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Section: Definition 1 ([26])mentioning

confidence: 99%

“…He stated the necessary conditions in terms of a local minimum principle and use of the Fischer-Burmeister function. Buldaev [14] used perturbation methods in optimal control problems. Numerical methods based on extended one-step methods were investigated in [15] for solving optimal control problems.…”

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confidence: 99%