针对直流调速系统，将单神经元自适应PID控制器与负载观测器有机结合，提出了一种基于单神经元的自适应速度控制方法。
An adaptive speed control scheme for DC drive system, which combines an adaptive PID controller based on single neuron with a load observer, is presented.
本文介绍了一种可互换模型参考自适应方法实现对电机转速和定子电阻的辨识，并将其应用于异步机的无速度传感器直接转矩控制中。
A mutual model reference adaptive method for the rotor speed and stator resistance identification is proposed in this paper to implement a speed sensorless direct torque control of induction motors.
该方法通过增大控制参数的数值，可以得到更快的参数自适应律和同步响应速度。
The method can obtain a faster update law of unknown parameters and a faster synchronization response rate by increasing control parameters.
通过计算机仿真及其在实用电梯上的试验，结果表明基于单神经元自适应PID控制的方法，对提高电梯速度的跟踪性能有较好的作用。
The results of simulation and experiments show that the single neuron adaptive PID control method is very good in improving following performance to ideal speed curve.
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.
介绍了全液压推土机行走控制的关键技术，重点给出了行走方向与速度控制及功率自适应控制等主要环节的控制策略和控制方法。
The key techniques of hydraulic bulldozer travelling control are introduced. The control strategies and algorithms of direction and velocity control, and power self-adaptive control are developed.
讨论了影响乘客舒适感和平层精度的电梯速度曲线，提出了一种基于神经元的自适应控制方法，理论和仿真结果证明了其可靠性及可行性。
Elevator speed curve is discussed in this paper. An adaptive control strategy based on neural network is presented. A practical case was given to show the feasibility, practicality and reliability.
介绍了异步电动机矢量控制系统神经网络速度控制器的设计方法；同时提出了将开环直接计算与模型参考自适应方法相结合的神经网络混合转速辨识模型。
And a new hybrid speed identification method is also proposed, which based on the neural network, combines the open loop estimator and the instantaneous reactive power model reference adaptive system.
经过深入分析和揭示问题的实质后，提出了另一种自适应律，该方法在没有影响原来控制效果的情况下，可以提高系统的响应速度。
After researching the essential problem, another adaptive rule, which can not only improve response speed of the system but also will not effect the original control performance, is presented.
将预测控制方法应用到有源噪声控制领域，给出了一种参数在线自适应算法，该算法的收敛速度不受次级声路径响应的影响。
An active noise self-tuning model predictive control approach is derived. An on-line learning algorithm is proposed for adjusting the uncertain model parameters.
将基于紧格式线性化的非参数模型直接自适应预测控制方法应用到直线电机速度和位置控制中。
The forming process is simplified to a discrete single input single output system and described by a non-parametric model.
将基于紧格式线性化的非参数模型直接自适应预测控制方法应用到直线电机速度和位置控制中。
The forming process is simplified to a discrete single input single output system and described by a non-parametric model.
应用推荐