结果表明，相对于常规PD控制器，该神经网络控制器具有自学习、自适应功能，位置跟踪获得了满意的控制效果。
The simulation results prove that the neural network controller has self-learning and self-adaptive ability by comparison with PD controller. The position tracking control obtains satisfactory effect.
对一类不确定非线性系统，包括不确定性机器人，提出一种自适应鲁棒迭代学习控制方案。
An adaptive robust iterative learning control scheme is developed for a class of uncertain nonlinear systems, including robotics as a subset.
针对一类单输入单输出不确定非线性重复跟踪系统，提出一种基于完全未知高频反馈增益的自适应迭代学习控制。
An adaptive iterative learning control approach is proposed for a class of single input, single output uncertain nonlinear systems with completely unknown high frequency learning gain.
鉴于模糊神经网络具有良好的非线性特性、学习能力、自适应能力和抗干扰能力，本文将模糊神经网络技术引入到高速公路入口匝道控制中。
Due to the traits of nonlinear, capacity of study, adaptivity and anti-interference, neural-fuzzy network is suitable for the control of ramp metering.
并针对某些学习应用提出了一种两阶段自适应控制逐一训练算法。
Using this algorithm, an adaptive learning controlling value is established according to the recent convergence error and its rate of change.
本文给出了利用自适应神经元学习、修改模糊控制规则的新方法。
This paper proposes a new method to learn fuzzy control rules using adaptive neural element.
在反馈学习算法的基础上，将模糊逻辑和神经网络自适应控制的结构结合在一起。
The neural network-based adaptive control and fuzzy logic are integrated based on feedback learning algorithm.
提出了一类基于神经元状态估计器的自适应广义极点配置控制，研究了该控制系统的网络结构和权值学习方法。
This paper presents a class adaptive pole assignment control of servo systems based on neural state estimation and develops the system structure and the weight learning algorithms.
仿真结果表明，相对于常规PI控制器，该神经网络控制器具有自学习，自适应功能，速度跟踪获得了满意的控制效果。
The results show that the neutral network controller has shelf-learning and self-adaptive functions, and has better control effect in speed tracking, compared with traditional PI controller.
该MNN网络能用于在线学习对象的动态特性，从而提供一种能提高整个控制系统性能的自适应控制实现策略。
The MNN can be used for on -line learning of the plant's dynamic characteristics and provide a kind of adaptive control strategy which can improve the whole control system's performance.
实验证明，此控制系统具有较强的自适应性与自学习能力，表明了该方案的正确性与实用性。
Experiment demonstrates that the system has good self adaptability and self studying ability, certifying the correctness and practicability of the proposed scheme.
该控制器不仅具有自学习自适应能力，而且具有自调整比例因子功能。
It has not only the learning ability and the adaptability, but also the self-adjusting factor function.
遗传算法的这些性质，已被人门广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。
The features of GA have been widely used applied in territories such as optimization, machine learning, treatment of signal, self-adoption control, artificial existence and so on.
该文给出了一种自适应神经元的控制方法，设计了神经元网络作为控制器的智能控制系统，给出了学习规则。
An adaptive neuron control method is presented. By use of this kind of controller, an intelligent control system is designed, and its learning rules are also presented.
目前这类算法已被广泛应用于机器学习，人工智能，自适应控制，人工神经网络训练，图像处理等各个方面。
This algorithms has been widely used in machine learning, artificial intelligence, adaptive control, artificial neural network training, Image processing, among other areas.
介绍了神经网络自学习鲁棒自适应控制器，该控制器可以应用在模型未知的控制系统中。
Introduction was made to a neural network robust adaptive controller, which can be applied in model unknown control system.
通过神经网络的自学习、实现PID控制参数的自适应调整。
The adapted-self tune-up for PID control was completed through learning-self of neural network.
该方法利用RBF神经网络的自学习、自适应能力自调整系统的控制参数。
This method uses the liability of self-study and self-adaptability of RBF network to turning parameters of system.
另外一个方面，离线仿真也是对控制系统的自适应和自学习的一个有益的补充，有利于控制系统的优化。
Another, Off-line Simulation is supplement of self_learning and adaptive in control system, it is propitious to optimization of control system.
利用神经网络的学习功能对控制器的隶属度函数及推理规则进行修正，以提高其自适应能力。
The membership functions and the inference rules in the controller are modified using the learning functions of neural network so that the adaptability of the controller is further enhanced.
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.
文中提出一种基于模糊自适应学习控制(FALCON)结构下新型的混合学习控制策略。
A new fuzzy adaptive learning control (FALCON), structure based mixture learning control is put forward in the paper.
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.
针对包装印刷传动位置伺服系统，介绍一种基于共轭梯度学习算法的神经网络自适应PID控制方法。
The paper proposes an adaptive neural network PID controller based on weighlearning algorithm using the gradient descent method for the AC position servosystem of binding and printing.
提出一种利用神经网络的自学习特性，对陀螺稳定平台的速度环进行自适应控制的方法。
Based on the self-learning property of neural network, an adaptive control method for speed ring of a gyroscope-stabilized platform is put forward in the paper.
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.
本文提出一种带有高斯模糊器的自适应模糊系统(GAF)，基于PID控制的成功经验数据，通过反向传播学习算法对其进行参数寻优。
This paper introduces a new adaptive fuzzy system with Gauss fuzzier (GAF), optimizing the parameter based on the data from PID by back-propagation algorithm.
本文提出一种带有高斯模糊器的自适应模糊系统(GAF)，基于PID控制的成功经验数据，通过反向传播学习算法对其进行参数寻优。
This paper introduces a new adaptive fuzzy system with Gauss fuzzier (GAF), optimizing the parameter based on the data from PID by back-propagation algorithm.
应用推荐