基于自适应逆控制方法设计了主汽温系统的双回路扰动消除系统。
Based on the methods of adaptive inverse control, double loops of disturbance canceling system are designed for the main steam temperature system.
在前馈部分，构造了一种基于神经网络的前馈控制器，用于主汽温系统的干扰抑制。
In feedforward, based on the neural network control theory, a feedforward controller is designed for disturbances overcoming of the control system.
仿真结果表明，该方案可较好地解决主汽温系统存在的内、外扰动问题，对主汽温系统的扰动消除具有较强的鲁棒性和自适应能力。
The simulation result shows that this method can solve the disturbance problems and has strong robustness and self-adaptability for disturbance canceling of the main steam temperature system.
对系统在多种工况下的仿真结果表明，所设计的系统在控制品质、鲁棒性方面明显优于主汽温常规PID控制系统。
Through simulation in various situations, it is validated that the control quality and the robustness of this control system apparently are superiors to the general PID system.
针对火电厂主汽温被控对象的大迟延、模型不确定性，设计了基于神经网络的主汽温控制系统。
In order to overcome the large delay and the uncertainty of the main-stream temperature object in fossil-fired power station, a control system based on neural network is proposed.
针对火电厂主汽温被控对象的大迟延、模型不确定性，设计了基于神经网络的主汽温控制系统。
In order to overcome the large delay and the uncertainty of the main-stream temperature object in fossil-fired power station, a control system based on neural network is proposed.
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