In this paper, the characteristics and advantages of neuro fuzzy intelligent control algorithm, which is an intersection of neural networks and fuzzy logic, are studied.
研究了将神经网络与模糊逻辑融合交叉而形成的神经网络-模糊智能控制算法的特点和优越性。
In this paper, a predictive control strategy based on neuro-fuzzy model is applied to Continuous Stirred Tank Reactor (CSTR) process, which has characteristic of highly nonlinearity.
针对具有高度非线性特性的连续搅拌反应釜(CSTR)控制过程，研究了基于神经模糊模型的预测控制策略。
Aiming at the problem of guided bombs in low precision, this paper presents a kind of intelligence control system of guided bomb based on Adaptive Neuro-Fuzzy Inference system (ANFIS).
针对目前制导炸弹命中精度低的问题，提出一种基于自适应神经模糊推理系统(ANFIS)的制导炸弹智能控制系统。
The control for speed limit on expressway is a nonlinear and time variable system, it is difficult to simulate with a mathematical model. A neuro-fuzzy network is proposed to solve the problem.
高速公路限速控制是一个非线性时变系统，难于用数学模型准确建模，提出一种模糊神经网络实现限速控制。
The fuzzy-neuro model-free control is one of the important areas in intelligent control.
模糊神经非模型控制是智能控制的一个前沿课题。
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.
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。
The intelligent control system consists of reference governor, neuro-fuzzy feedforward controllers, fuzzy feedback controllers and fossil-fuel power unit (FFPU).
该系统包括设定值调节器、神经网络模糊前馈控制器、模糊反馈控制器和单元机组。
Motivated by the designing idea of conventional feedforward control, an adaptive feedback-feedforward control scheme based on neuro-fuzzy system is proposed.
在前馈控制器设计思想的启发下，提出了一种基于神经模糊系统的自适应前馈-反馈控制系统。
In this paper, we present an Adaptive Network-based fuzzy Inference system (ANFIS), based on a neuro-fuzzy controller, as a possible control mechanism for a ship stabilizing fin system.
提出基于自适应网络模糊推理系统(ANFIS)的神经模糊控制器作为船舶减摇鳍系统的控制装置。
Recently, Neuro-fuzzy Control base on the Neural Network Theory and Fuzzy Logic System was used widely and successfully.
近年来，基于神经网络和模糊逻辑的神经模糊控制得到了广泛的应用。
Recently, Neuro-fuzzy Control base on the Neural Network Theory and Fuzzy Logic System was used widely and successfully.
近年来，基于神经网络和模糊逻辑的神经模糊控制得到了广泛的应用。
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