软件设计首先完成了PWM信号的输出与时序控制，并设计了键盘输入功能模块、LED显示功能模块、电流电压信号采样功能模块，以及模糊神经算法自学习软件功能模块。
The software design implemented PWM output and sequence control module, keyboard input module, LED display module, current and voltage sampling module and fuzzy neural algorithm self study module.
针对直接驱动直线式交流伺服系统，提出了一种基于模糊自学习的滑模变结构控制方案。
This paper presents a sliding mode variable structure control (SMVSC) method based on fuzzy self-learning for a direct-drive AC Lin ear servo 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.
二是基于机器人重复控制的学习机理，提出了一种船舶航向自学习型模糊控制系统，分析了该系统的特点。
The other is ship course self-studying fuzzy control system, which is based on the learning mechanism of robot repetition control. The thesis analyses the system 's characteristic.
本文提出一种基于基因算法优化的自学习模糊控制器的设计。
This paper proposes a design of the self adaptive learning fuzzy controller based on Genetic Algorithms optimization.
仿真结果表明，所设计的神经网络模糊控制器具有自学习、自适应等优点，达到了在线控制的目的。
The result of simulation shows that this neural network fuzzy controller features self-learning and self-adaptive capabilities, and the purpose of on-line control is accomplished.
新控制器在控制过程中借助模糊神经网络的自学习算法实现控制参数的在线调整。
The parameters of new controller can be adjusted on line based on the ability of fuzzy ne ural network.
基于模糊t - S模型，提出一种具有自学习能力的模糊方法用于批过程建模和最优控制。
Based on fuzzy T-S model, a fuzzy method with self-learning capability for batch process modeling and optimal control is presented.
将自适应模糊控制理论引入振动控制工程领域，提出了一种基于模糊逻辑系统的在线自学习控制方法。
In this paper, adaptive fuzzy control theory is led into the research field of vibration control engineering, and an on line self study method based on fuzzy logic system is proposed.
将基于滑模控制的自学习模糊控制应用于挠性卫星的姿态稳定控制中。
The self-learning fuzzy control based on sliding mode control is applied to the attitude stabilization of flexible satellites.
本文通过简化模糊控制算法中的模糊关系，建立了一种运算量少，易于实现实时控制的自学习模糊控制算法。
A self learning fuzzy control algorithm is presented in this paper. The algorithm with a simplified fuzzy relation can save computation.
应用一种变结构神经网络算法对初始化的模糊规则进行调整，提高模糊控制规则的自学习和自适应能力。
A kind of variable structure neural network algorithm is adopted to adjust fuzzy rules, and improves the ability of self-studying and self-adjusting in fuzzy control rules.
该系统依靠模糊控制理论提高了灵敏度，减少了误报率，并结合神经网络具有自学习功能的特点，提高了整个系统的智能化程度。
The system would reduce the malfunction rate with high sensitivity. Also the neural network has function of self-learning, which would raise the degree of intelligence of the system.
本文引用人工智能原理，在模糊控制器的基础上，设计出一种自学习智能控制器。
The artificial intelligence principle is introduced. Based on a fuzzy controller, a self-learning intelligence controller is designed.
将神经网络与模糊控制相结合，实现了模糊控制器的自学习和自适应。
Combine the neural network with controlling fuzzy control, the ones that have realized the fuzzy controller are from the self-study and self-adaptation.
建立了伺服感应电动机DTC控制模型，其中速度观测器采用文中提出的自学习模糊速度观测器。
Then, a DTC induction motor servo control simulation model is established, which adopts the self-learning fuzzy in velocity observer.
但由于模糊控制技术本身存在着建立模糊规则比较困难，自适应能力和自学习能力差等缺点。
But building the fuzzy rules is hard, and the ability of self-adapting and self-study are poor in the fuzzy control technology.
这种自适应模糊控制器基于模糊推理规则自学习和自调整的控制算法，无需知道太多的专家控制规则，因此解决了制冷系统MIMO模糊推理规则难以获取的问题。
This adaptive fuzzy controller is based on fuzzy inference rules self-learning without needing so much expert control rules, which solves the problem of acquiring MIMO fuzzy inference rules.
由于模糊观测器的模糊控制规则主观性较强，因此设计自学习模糊速度观测器，并给出了详细的算法和流程。
Since the fuzzy observer has a strong subjectivity in fuzzy control rules, self-learning fuzzy velocity observer is produced to present detailed algorithm process.
由于模糊观测器的模糊控制规则主观性较强，因此设计自学习模糊速度观测器，并给出了详细的算法和流程。
Since the fuzzy observer has a strong subjectivity in fuzzy control rules, self-learning fuzzy velocity observer is produced to present detailed algorithm process.
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