Which is based on the proposed RBF neural network inverse controller and a proportion differential controller.
并提出一种基于RBF神经网络逆控制与比例微分控制相结合的双模控制策略。
Choosing a training method is very important when using neural network to obtain the model and the inverse model of the nonlinear object.
在使用神经网络完成非线性对象的模型和逆模型时，选择的训练方法很重要。
The results of simulation show that the existing control problem of the plant can be successfully solved by neural network, adaptive inverse control and the result is good.
仿真结果表明，神经网络、自适应逆控制方法可以成功地解决装置中现有的控制问题，并取得良好的效果。
The proposed controller combines the advantages of neural network and inverse system control, and can compensate the influence of uncertainty and nonlinearity.
该方法结合了神经网络和逆系统控制的优点，能够克服系统中的不确定性和非线性因素。
An innovative robot calibration approach: inverse robot calibration based on neural network, is proposed in this paper, based on the analysis of traditional calibration approach.
在分析传统机器人位姿标定方法的基础上，提出了一种新的机器人标定方法：基于神经网络的逆标定方法。
Neural network is used in this paper to solve the problem of kinematics and inverse kinematics in kinematical control of spatial redundant robots.
针对空间冗余机器人运动学控制中正、逆运动学求解的复杂性，采用神经网络从两方面解决这一问题。
Based on the property of the system inverse model, an integral approach to nonlinear compensation of temperature measuring system with thermistor based on neural network is presented.
从系统逆模型补偿出发，基于神经网络提出一种更加完备的热敏电阻测温系统非线性校正方法。
The inverse mapping is achieved through BP network, and neural network modul is constructed for designing process parameters.
通过误差逆传播(BP)网络实现了逆映射，建立了工艺参数设计的神经网络模块。
Based on the new ANN (artificial neural network) inverse system control method, the AC variable frequency speed control system is analyzed and experimented.
本文运用神经网络逆系统这一新的控制策略，对异步电机变频调速系统进行可逆分析与控制试验。
A direct inverse model controller of fuzzy neural network with changeable structure based on t s inference is presented in this paper and it is used to the motion control of mobile robot.
本文提出一种基于T -S模型的变结构模糊神经网络直接逆模型控制器，并将其应用于移动机器人的运动控制中。
An inverse controller based on neural network for single inverted pendulum is proposed.
给出了单级倒立摆的一种神经网络逆模控制方案。
Then, aiming at the existing problem, the algorithm of dynamic recurrent neural network, RBF neural network and adaptive inverse control is studied in the paper.
接着，结合其存在的问题，对动态递归神经网络、R BF神经网络和自适应逆控制进行了算法研究。
Based on the model parameter identification theory in inverse problem, a neural network model for constitutive law of clay under multiple stress paths is set up through artificial neural network.
基于反问题中的模型参数辩识理论，通过人工神经网络，建立了考虑应力路径影响的粘土的神经网络本构模型。
In the algorithm, the radial-basis function neural network (RBFNN) is utilized as forward model, and the IGLSA is used to solve the optimization problem in the inverse problem.
该算法中，径向基函数神经网络(RBFNN)用作前向模型，IGLSA用于求解逆问题中的优化问题。
Based on the thought of inverse system control, a method of on-line self-learning control strategy was proposed, which combines inverse control based on RBF neural network with PID control.
基于逆动力学控制的思想，提出一种RBF神经网络逆控制与PID控制相结合的在线自学习控制方案。
In this paper, a neural network internal model control scheme was studied, which was based on the design of inverse system.
本文研究了基于逆系统方法的神经网络内模控制。
A direct inverse control scheme of FCMAC neural network is presented for vector control AC servo system. The principle analysis and the design realizing process of the system are given in detail.
本文针对矢量控制交流伺服系统，提出了一种模糊小脑模型神经网络直接逆控制的方案，给出了较详细的原理分析及实现过程。
In the condition of selecting the learning samples properly, the artificial neural network has the obvious advantage in the inverse designing the electronic lens.
可以看到在较好的选取学习样本情况下，神经网络技术在电子透镜的逆设计中有着明显的优越性。
Then the neural network based inverse model of the inverted pendulum is trained.
然后，以这些数据为基础训练倒立摆的神经网络逆模型；
The system identifier based on RBF neural network which applies nearest neighbor clustering algorithm realizes the identification of the inverse dynamic system model.
辨识器采用RBF神经网络结构和最近邻聚类算法，实现了对系统逆动力学模型的动态辨识。
In this paper, several artificial neural network based models of solving inverse eigenvalue problem and their characters are studied. These models are direct, indirect and optimization inverse models.
研究了特征值反问题求解的几种神经网络模型：直接逆模型，间接逆模型，优化方法模型，指出了各种方法的应用范围。
Meanwhile a HCMAC neural network is fabricated to replace the complex calculation of the inverse Jacobian mapping.
同时，利用分层神经网络代替视觉空间到任务空间的映射，避免了复杂的逆矩阵计算。
A forward model and an inverse model of a MR damper were established by using BP neural network.
采用BP神经网络，建立了磁流变阻尼器的正向模型和逆向模型。
The method, which combines the advantages of artificial neural network and genetic algorithm, is an universal one of solving inverse eigenvalue problem.
计算结果及分析表明它是求解一切特征值反问题的有效方法。
Methods based on BP neural network and RBF neural network were studied to solve inverse kinematics. The training samples were obtained through off-line numerical method with high precision.
通过离线的迭代算法生成高精度的样本点来训练神经网络，使用动量法、变学习率法和共轭梯度法提高BP网络的收敛速度。
An inverse model of the sensor is obtained based on neural network trained by the sensor's output and the actual sensed ice thickness.
以传感器的双光路输出信号及实际冰厚值训练神经网络，建立了传感器的逆向模型。
An inverse model of the sensor is obtained based on neural network trained by the sensor's output and the actual sensed ice thickness.
以传感器的双光路输出信号及实际冰厚值训练神经网络，建立了传感器的逆向模型。
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