本文围绕非线性系统的模糊神经网络控制问题，展开研究，设计了一个自适应模糊神经网络控制系统。
This paper mainly focused on the problem of fuzzy neural network control of non-linear system and got into further study and then a self-adaptation control system of fuzzy neural network was designed.
在对SZ绞合成缆机设备组成简介的基础上，设计了基于模糊神经网络的SZ绞合成缆机现场总线控制系统。
After brief introduction of equipments of SZ stranding machine for optical fibers, this paper designs SZ stranding machine field bus control system based on fuzzy neural network.
这种方法把模糊控制和神经网络相结合进行控制系统的建模。
This way combines fuzzy control with neural networks to build the model of control system.
提出了一种带模糊补偿的神经网络辨识器，并应用在某型涡扇发动机转速控制系统中。
A new neural network algorithm with fuzzy logic compensation was proposed and applied to an aero-engine rotating speed control system.
仿真结果表明该方法精简了网络的结构，减少了训练的时间，为模糊神经网络用于实时控制系统提供了可能的条件。
The method can simplify the structure of network and reduce the time of training that supplies the possibility that FNN is used in realtime control system.
本文提出一种模糊神经网络自学习控制方法，并应用于窑炉温度控制系统中。
Based on fuzzy neural network, this paper presents a self learning controller used to industrial kiln temperature system.
此外，通过遗传算法对模糊神经网络的学习速率和惯性系数等进行了优化，为控制系统实现最优控制提供了有力保证。
In addition, the paper makes use of Genetic Algorithms to optimize learning rates and inertia coefficients of Fuzzy-neural network, which can ensure that the controller achieves optimization control.
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.
控制系统的硬件采用了DSP芯片，以保证系统的实时性；软件采用了模糊-神经网络算法，以克服系统模型的不确定性。
DSP chip is applied in hardware design to ensure real-time performance of control system, and fuzzy-neural network algorithm is adopted to overcome uncertainness of control model.
文章着重介绍模糊逻辑控制、神经网络控制以及它们的交叉结合的神经网络-模糊控制系统及其应用与设计。
Emphasis is put on the fuzzy logic control, neural network control, and both crossed neural network with fuzzy control system along with its application and design.
仿真结果表明了模糊神经网络观测器可实现对定子电阻的精确检测，从而提高直接转矩控制系统的低速性能。
Simulation results show that this fuzzy-neural network estimator can precisely measure the value of resistance and improve the low-speed performances of DTC system efficiently.
通过对控制系统的过程模拟，提出一种模糊神经网络最优控制方案。
An optimal control scheme based on fuzzy neural network is proposed through simulating the process of the control system.
应用模糊神经网络PID控制技术，建立了高分子聚合物反应温度控制系统。
The temperature control system for macromolecule polymer reaction is designed by the method of Fuzzy_Neural PID control.
针对复杂工业过程控制系统的特点，提出一种专家系统和模糊神经网络相结合的二级协调智能控制系统。
By integrating expert system with fuzzy neural network, a new type of two-level coordination intelligent control system used in complex industrial processes is proposed in this paper.
然后应用一种改进的模糊神经网络自适应控制系统，设计了TCBR的控制器。
Then, applying adaptive control system based on improved fuzzy neural network, a TCBR controller is designed.
在此基础上提出了基于模糊神经网络控制的调距桨控制系统的设计，仿真试验结果表明了调距桨控制系统设计的合理性。
The controllable pitch propeller control system based on fuzzy and neural network control is proposed, the result shows that the system design is feasible and effective.
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.
本文设计并实现了一种基于神经网络和模糊控制的车载厢体风机智能控制系统。
This article has designed and Implement one kind of air blower intelligence control system on compartment of automobile based on nerve network and fuzzy control.
推导了逆变点焊过程控制模型，并构建了逆变点焊模糊神经网络恒电流控制系统结构。
A controlling model of inverter spot-welding process and a fuzzy neural network configuration about inverter spot-welding with constant current control were built in this paper.
在此基础上，结合列车运行安全控制的实际情况，加入直控神经元，构造了直控模糊神经网络控制（ZFNN）模型来保证控制系统符合故障-安全原则。
On the basis of, some direct-control neurons are added to the FNN, and then a new FNN model is produced which is named as ZFNN.
在玻璃钢缠绕设备的控制系统中，设计了一种新型模糊神经网络控制器。
A new fuzzy neural network controller is designed in the winding machine.
本文以机器人为研究对象，针对其强耦合、非线性、多变量等特点，提出了一种模糊神经网络控制器组成的控制系统。
This paper USES robot as researched object that is of strong coupling, nonlinear and multi-variable characters. A control system is proposed which consists of a fuzzy neural network controller.
在控制系统中，将贝叶斯概率引入到模糊rbf神经网络中，增强了系统的推理能力，提高了飞机各个航道位置的模拟伺服精度。
In the control system, Bayes probability is introduced in the fuzzy RBF neural network and it intensity the inference ability and increase the servo precision.
针对控制系统中模拟电路故障诊断时的不确定性问题，提出了将模糊理论和神经网络相结合的方法。
In order to handle the uncertainties in fault diagnosis of analog circuits used in the control system, a method, which combines fuzzy theory and neural network, was proposed.
并与国内外研究较多的无刷直流电机的基于自适应PID、模糊控制、神经网络控制、PID控制的双闭环控制系统进行仿真对比实验。
Simulation experiment compared with the double-loop motor subject to adaptive PID control, fuzzy control, neural-network control and conventional PID control is presented.
在综述了现有的各种悬架控制方法基础上，着重论述了模糊控制、神经网络控制、模糊神经网络控制等方法在车辆悬架控制系统中的应用。
On the basis of summing up existing methods for vibration control on the suspension systems, emphases are put on the discussion of application of fuzzy control, neural network control…
在综述了现有的各种悬架控制方法基础上，着重论述了模糊控制、神经网络控制、模糊神经网络控制等方法在车辆悬架控制系统中的应用。
On the basis of summing up existing methods for vibration control on the suspension systems, emphases are put on the discussion of application of fuzzy control, neural n...
阐述了在导弹系统存在不确定性情况下，基于自适应反演控制技术和模糊神经网络理论，提出了一种导弹滑模控制系统设计方法。
Based on adaptive backstepping control techniques and fuzzy-neural theory, a sliding mode control scheme is proposed for missile control systems with uncertainties.
阐述了在导弹系统存在不确定性情况下，基于自适应反演控制技术和模糊神经网络理论，提出了一种导弹滑模控制系统设计方法。
Based on adaptive backstepping control techniques and fuzzy-neural theory, a sliding mode control scheme is proposed for missile control systems with uncertainties.
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