The design of quantum system control is a key task to a powerful quantum information technology. In practical, traditional quantum system control methods often face different constraints, and are easy to cause both leakage and stochastic control errors under the condition of limited resources. Reinforcement learning has been proved as an efficient way to complete the quantum system control task. So a quantum system control method based on enhanced reinforcement learning (QSC-ERL) is proposed. A satisfactory control strategy is obtained through enhanced reinforcement learning so that the quantum system can be evolved accurately from the initial state to the target state. According to the number of candidate unitary operations, the three-switch control is used for simulation experiments. Compared with other methods, the QSC-ERL can achieve high fidelity learning control of quantum systems and improve the efficiency of quantum system control.