In the process every motor just need to hold its velocity, so we use single neural PID controller.
这时只需各道电机保持过渡过程结束时的转速运行，采用单神经元pid控制器。
Experimental results show that the neural PID controller can efficiently track the movement of the joint and it is an appropriate controller for this kind of joint.
试验结果表明应用神经pid控制器能够有效地跟踪关节的运动轨迹，是适合这种关节的控制器。
The result shows that the neural PID control strategy is more robust than conventional one and is suitable for the control of variable-frequency air conditioning systems.
结果表明，神经元PID控制较常规PID控制具有更好的鲁棒性，更适合用于变频空调系统的控制中。
The parameters of the neural network PID controller are modified on line by the improved conjugate gradient.
并用这种改进的共轭梯度法对神经网络PID控制器参数实现在线修正。
This paper designs a diesel controller which contains a parameter_optimizing PID controller and a neural network controller based on model of diesel.
针对柴油机模型自身的特点，设计了一种神经网络与参数自寻优pid控制相结合的控制器。
After the success in decoupling, single neural cell self-adapting PID is adopted to control nonlinear object. The simulation results show that the control strategy gets better effects.
当解耦器训练结束后，对于非线性对象采用单神经元自适应PID来进行控制，仿真结果表明，此控制方案效果较好。
Aiming at the problem of traditional PID control algorithm is difficult to get ideal control effect, an adaptive PID control algorithm based on BP neural network is proposed.
针对传统的PID控制算法很难获得比较理想的控制效果的问题，提出一种基于BP神经网络的自适应pid控制算法。
Combined CMAC neural network control algorithm with PID control algorithm, a parallel control system for Marine generator excitation system was designed.
结合CMAC神经网络控制算法与PID控制算法设计了船舶发电机励磁并行控制系统。
Last we apply the neural network PID control method to temperature control system for a water bath, experimental results show that the present method provides an excellent control results.
最后，将神经网络PID控制器取代基本PID控制器用在浴室水箱温度控制中，仿真结果表明这种控制方法有很好的控制效果。
A new neural network controller is proposed based on the PID controller structure. Its basic structures and learning algorithm are analysed.
根据PID控制结构提出了一种新型神经网络控制器，对其基本结构和学习算法等进行了分析。
In this paper, according to nonlinear and time-varying parameter of ship maneuvering, the scheme of neural network adaptive PID control is proposed.
本文针对船舶操纵这种非线性、时变参数控制对象，提出了一种采用神经网络自适应PID控制方案。
The arithmetic of PID control based on neural network can obtain small speed overshoot and strong anti-interference feature.
在抗干扰特性方面，基于神经网络的PID控制算法有较小的波动，而且调节时间较短；
To improve robustness of control system, the paper analyses the influence of nonlinear factors and introduces the neural network PID auto adaptive control to reduce the influence.
为了增强系统的鲁棒性，论文在分析非线性因素对系统的影响后，利用神经pid自适应控制实现了对这些因素的有效抑制。
In this paper, a new automatic tuning method of PID controller based on dynamic neural network is proposed and an online parameter tuning algorithm is given out.
提出一种基于动态神经网络的PID控制器，给出pid参数在线自整定学习控制算法，并进行了算法仿真研究。
So this article adopt PID control tuned by BP neural net.
因此，本文采用BP神经网络整定的PID控制。
Based on the study of BP neural network and PID controller, a single neuron adaptive PSD algorithm is presented.
在对BP神经网络PID控制器系统研究的基础上，提出了单神经元的自适应PSD算法。
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.
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 PID controller based on BP neural networks is designed to realize control parameter self-learning and self-adjusting.
设计了基于BP神经网络的PID控制器，实现PID控制器参数自学习、自整定。
A neural network PID control algorithm is presented to improve the PID adaptive control performance.
为提高PID控制的自适应性能，提出了一种神经网络PID自适应控制算法。
The part of neural network of the intelligent self-tuning PID controller based on BP network learns the learning sample.
由设计出的基于BP神经网络的智能自整定PID控制器的神经网络部分对学习样本进行学习。
The emulational results show that the improved BP neural network PID enables the convergence to be faster and the system has strong robustness and self-adaptive.
仿真结果表明，改进BP神经网络PID使收敛变得更快，而且系统具有较强的鲁棒性和自适应能力。
The text has discussed the neural network PID controller mainly.
本文主要研究了神经网络PID控制器。
A new type of adaptive PID controller using diagonal recurrent neural network (DRNN) is presented. An on-line learning algorithm based on PID parameter self-tuning method is given.
提出了一种基于对角回归神经网络的PID控制器结构，给出了PID参数在线自整定的学习控制算法。
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。
Based on the mathematic model of PMSM, a combination of an improved BP neural network and a general PID controller is used in its speed control system.
在分析永磁同步电机数学模型的基础上，采用改进型BP神经网络与传统PID控制相结合作为速度控制器，应用于永磁同步电机调速系统中。
Finally, this paper presents an improved model of the magnetic chain, using a single neural network PID controller to adjust the stator flux, and set up the corresponding flux estimation model.
最后本论文提出了一种改进的磁链模型，引入了单神经元网络PID控制器来调节定子磁链，并建立了相应的磁链模型。
Analyzing the integral splitting PID algorithm, and melting the wide-used PID controller and the automatic learning neural network, got a PID control algorithm based on the BP network.
分析了积分分离pid控制算法，在此基础上，将应用最广泛的PID控制器与具有自学习功能的神经网络相结合，得到了基于BP神经网络的PID控制算法。
In view of the nonlinearity and parameter time-varying uncertainty of vehicle dynamics, a novel algorithm, i. e. single neural adaptive PID control strategy, is propsed for vehicle direction control.
针对汽车方向动力学控制存在的非线性和参数时变不确定性问题，提出了一种新的基于单神经元的汽车方向自适应pid控制算法。
In view of the nonlinearity and parameter time-varying uncertainty of vehicle dynamics, a novel algorithm, i. e. single neural adaptive PID control strategy, is propsed for vehicle direction control.
针对汽车方向动力学控制存在的非线性和参数时变不确定性问题，提出了一种新的基于单神经元的汽车方向自适应pid控制算法。
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