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In this paper, a control method based on fuzzy systems is presented to drive and keep state of a sample quantum system into a pre-defined region. The considered quantum system is a third-order quantum system and the model of the system is bilinear model. In addition, measurements of the system in the defined region are obtained at each times by considering the effects of such measurements in the internal state of the system. The effect of unwanted inputs and structural uncertainties also are considered as bounded uncertainties in the system’s Hamiltonian. In this paper, it is assumed that the initial state of the system is determined and internal state system are available as the feedback signals at each instant of time. In the proposed control approach, an acceptable region is firstly defined around the desired final state. Then, an adaptive neuro-fuzzy inference system improved using imperialist competitive algorithm is used for driving the system’s state toward the desired final state within this region. In addition, a fuzzy supervisor is utilized to adjust a control parameter for preserving the state of the quantum system inside the defined region. Simulation results, obtained by applying the proposed method to a sample third-order quantum system in presence of bounded uncertainties show the applicability and effectiveness of the method for controlling the quantum systems.

Keywords: Quantum systems, Fuzzy controller, Improved adaptive neuro fuzzy inference systems, Imperialist Competitive Algorithm

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