| 1. | State feedback control with neural network compensator
神经网络补偿的状态反馈控制 |
| 2. | Nonlinear friction compensation based on neural networks for the positioning table
定位平台非线性摩擦的神经网络补偿 |
| 3. | Learning approach to compensate machine tools thermal deformation based on neural network
神经网络补偿机床热变形误差的机器学习技术 |
| 4. | A design method for generalized discrete model reference adaptive control system based on the compensation via a neural network
基于神经网络补偿的广义离散模型参考自适应控制系统设计 |
| 5. | Second , the thesis describes an adaptive reconfiguration method for augmenting an exist linear controller by an artificial neural network
其次，提出了一种神经网络补偿原有线性控制器的自修复飞行控制方法。 |
| 6. | A linear state - space model is modeled for the system identification and prediction at the tangent space of working point . the errors of modeling and
在局部的切空间上对系统进行线性建模和预测,同时利用在线学习的神经网络补偿局部线性模型的建模和预测误差。 |
| 7. | The paper tries bp and rbf two kinds of commonly used neural networks compensation model mainly , has compared with many kinds of networks and learning algorithms through the instance
本文主要尝试了bp和rbf两类常用的神经网络补偿模型，通过实例比较了多种网络学习算法。 |
| 8. | In view of chaotic systems composed of a sum of a linear and nonlinear part , a compensative control method using radial basis function networks is proposed , the rbf networks trained can eliminate the nonlinear part of the chaotic system , the resulting system is dominated by the linear part
然后针对大多数混沌非线性系统由线性函数和非线性函数两部分构成的特点，用rbf网络补偿系统非线性部分，使原系统变成近似线性系统，再结合线性状态反馈控制技术，对lorenz方程和duffing振子进行了非线性补偿控制。 |
| 9. | While with the super hige voltage power network gradually built and the structure of system becoming more complex , the calculation time of optimization increases when the number of buses that need reactive power compensation is relatively large . especially , when the positions of compensation are uncertain , selecting the position of compensation can reduce time when reactive power optimizing
而且随着超高压电网的逐步形成，系统结构日趋复杂，需要安装无功补偿设备的母线比较多的时候，优化计算所需的时间将加长；尤其是在网络补偿位置不确定的情况下，无功补偿点的选择就成为无功优化计算前节约时间的有效措施。 |
| 10. | In order to improve measurement precision and display fidelity of the instrument , three new methods of nonlinear calibration of thermal instruments , which are based on intelligent control theory , are presented in this paper , such as nonlinear compensation of zr02 oxygen measurement instrument using bp nn , nonlinear calibration of temperature measurement sensors using cmac nn and nonlinear identification of throttle flow meter using ga . these methods prove to be not only simple but also effective
火电厂热工仪表普遍存在非线性特性，为了提高参数测量的准确度和仪表显示的精确度，基于智能控制理论，文中提出了热工仪表非线性校正的新方法： bp神经网络补偿氧化锆氧量计非线性特性的方法、 cmac神经网络校正测温传感器非线性特性的方法、遗传算法辩识节流式流量仪表非线性特性的方法。 |
