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根据逆系统理论分别分析了以机端电压和功角为被控量的励磁系统的可逆性 ,并采用不同的神经网络逆系统结构实现了对单目标量的励磁控制。针对单目标励磁控制不能够同时改善功角稳定性和机端电压稳定性的不足 ,在以机端电压为被控量的神经网络逆系统结构中引入功角偏差反馈信号 ,设计了多目标神经网络励磁控制器。研究结果表明 ,应用该方法能够实现多目标励磁控制 ,综合性能优于单目标的神经网络逆系统控制方法和常规PSS控制方法
According to the inverse system theory, the reversibility of the excitation system with terminal voltage and power angle as the controllable quantity is analyzed respectively. Different kinds of neural network inverse system structure are used to realize the excitation control of single target quantity. Aiming at the shortcomings that the single-target excitation control can not improve both the power angle stability and the terminal voltage stability at the same time, the power angle deviation feedback signal is introduced into the inverse system structure of neural network whose terminal voltage is controlled. Network Excitation Controller. The results show that this method can be used to achieve multi-objective excitation control, the comprehensive performance is better than single-objective neural network inverse system control method and conventional PSS control method