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Abstract:   (249 Views)
Based on learning control methods and computational intelligence, control of quantum systems is an attractive field of study in control engineering. What is important is to establish control approach ensuring that the control process converges to achieve a given control objective and at the same time it is simple and clear. In this paper, a learning control method based on genetic quantum controller approach is presented. For tracking a time variant function trajectory, in a closed quantum system, the presented controller is used. For this purpose a constrained optimization problem, based on minimization of difference between a given trajectory and system states subject to an iteration relation of the dynamical solution be satisfied, is designed. According to high convergence rate in quantum genetic algorithm, a quantum genetic algorithm for solving the optimization problem is used. A stochastic measure for observation the initial population is used. Efficient an optimal tracking, with at least tracking errors and at least learned chattering are advantages of the presented method. A couple of examples for demonstrating the advantages are simulated. Simulation results reflect the good performance of the proposed method for controlling the quantum systems.
     
Type of Article: Research paper | Subject: Special
Received: 2016/12/15 | Accepted: 2018/09/4

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