首页> 外文会议>ISTM/2007;International symposium on test and measurement >The Robust Control Method Research of a Combined Controller Design with QFT and PID Based on BP Neural Network
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The Robust Control Method Research of a Combined Controller Design with QFT and PID Based on BP Neural Network

机译:基于BP神经网络的QFT与PID联合控制器设计的鲁棒控制方法研究。

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For the plant with uncertainty and high non-linearity, this paper puts forward a new combined controller design method with quantitative feedback theory and PID controller based on BP neural network. First, a method combined the BP neural network and the tradition PID control is developed, an initial controller is given. Then when the controller quality can not be improved effectively by tuning close-loop weighting function ,QFT is used to shape an open-loop transfer function according to the performance index bounds. The shaping has transparency in Nichols Chart and tailor characteristic on special frequency.The intermediate frequency characteristic of system is controlled by turning ξ and n ω .The high frequency performance is compensated in the QFT framework. The simulation result reveals that this method can generalize to design the control system in same uncertainty and high non-linearity system.
机译:针对具有不确定性和高非线性度的工厂,提出了一种基于定量反馈理论和基于BP神经网络的PID控制器的组合控制器设计新方法。首先,提出了一种将BP神经网络与传统PID控制相结合的方法,给出了初始控制器。然后,当通过调节闭环加权函数不能有效地提高控制器质量时,可根据性能指标范围,使用QFT对开环传递函数进行整形。整形在Nichols图表中具有透明性,并且可以在特殊频率上进行剪裁。系统的中频特性通过转动ξ和nω进行控制。在QFT框架中补偿了高频性能。仿真结果表明,该方法可以推广到设计具有相同不确定性和高非线性系统的控制系统。

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