介绍一种基于模糊神经网络的热处理电加热炉控制系统。本系统操作方便、运行可靠，具有较强的鲁棒性和可靠性。
The paper introduces a control system of heating process furnace based on the fuzzy neural-network. The system has advantages of simple operation, strong robustness and good reliability.
仿真实验结果表明，具有自适应神经网络的模糊推理系统控制的异步电机矢量控制系统不仅动态和稳态性能都得到提高，而且具有较强的鲁棒性。
Simulation results show that the induction motor vector control system with adaptive neuro-fuzzy inference system can improve the static and dynamic performance of the motor and has good robust.
利用动态模糊神经网络控制器对并联平台的轨迹跟踪控制进行了仿真，结果表明此控制算法具有较好的跟踪性能和较强的鲁棒性。
The proposed DFNN controller was applied on tracking control system of 6-dof parallel platform, and the results show that this method has better tracking performance and robustness.
利用动态模糊神经网络控制器对并联平台的轨迹跟踪控制进行了仿真，结果表明此控制算法具有较好的跟踪性能和较强的鲁棒性。
The proposed DFNN controller was applied on tracking control system of 6-dof parallel platform, and the results show that this method has better tracking performance and robustness.
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