并设计了车道保持系统在线学习控制结构模型，为下一步实现真正的在线学习控制提供了理论基础。
Structure model of online learning control for lane keeping system is designed. It provides the theoretical fundament for further study on online learning control in the future.
将模型参考控制和重复控制相结合应用到多通道电液力同步加载系统中，提出了一种在线学习控制的新方法。
Model reference control and repetitive control were applied in multi-channel electric hydraulic synchron-force servo loading system, and a new control method based on online learning was put forward.
如果学习者的在线学习不能控制自我，他们不会从网上学习中受益。
If the learners of online learning can not control themselves well, they will not benefit from online learning.
仿真结果表明该控制策略的可行性，并且可以有效缩短在线学习时间。
The simulation results present that the proposed control strategy is valid and the on-line learning time is abbreviated as well.
利用神经元的自学习功能实现神经元控制器的在线学习，并以神经元控制器作为交流伺服系统的位置调节器；
The neuron controller with its self-learning ability can realize the on-line learning algorithm, and it is adopted as the position controller of the AC servo system.
介绍了余热处理计算机控制系统的在线温度预报模型、设定模型和参数跟踪自学习模型的建立方法。
The method of establishing on-line temperature prediction model, set point model and parameter tracing self-learning model of computerized heat recovery processing control system is introduced.
该控制器利用神经网络在线学习具有多变量耦合、非线性及不确定性的复杂的焊接动态过程的控制规则，实现PID参数的自动整定。
The controller can learn, on line, the control rules of the complex dynamic process with multivariable coupling, nonlinear and uncertainty, so that the PID parameters are tuned automatically.
与一般SPC系统相比，本系统不仅可以在线检测过程异常，对各种控制图异常模式还具有实时学习、在线识别功能。
Contrast to these common SPC systems, it can not only detect the unnatural process behavior on line, but can also learn and identify these unnatural patterns on control charts at the same time.
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.
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.
新控制器在控制过程中借助模糊神经网络的自学习算法实现控制参数的在线调整。
The parameters of new controller can be adjusted on line based on the ability of fuzzy ne ural network.
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.
本文提出了基于高斯基函数CMAC在线学习的控制方案，并给出了相应的学习算法。
In This paper, an on-line learning controller based on CMAC with Gauss Basis Function Neural Network is presented, and its algorithm is discussed.
DRNN控制器是根据GMA的滞回特性构造的，通过反馈误差学习方案在线学习GMA的逆滞回模型。
The DRNN controller was constructed based on the hysteretic characteristics of the GMA, and on-line learned the inverse hysteresis model of the GMA by the feedback-error learning scheme.
该网络通过学习记忆PID参数调整的基本规则，实现了PID控制器参数的在线调整。
The network is used to remember adjusting rules of PID parameters by learning so the network can adjust PID parameters on line by rules.
基于VHDL设计该控制器，重点在于CMAC的在线学习算法实现和控制器模块的闭环仿真测试。
Controller is designed based on VHDL, the research keys are the implementation of the on-line learning algorithm of CMAC and the closed-loop simulation test of the controller.
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。
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.
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 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.
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。
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.
该控制方法基于神经网络并结合强化学习的自适应能力，通过神经网络的在线学习对车速进行跟踪控制。
Based on neural network and combined with adaptive capability of reinforcement learning, it can execute velocity tracking control through online learning of neural network.
针对短行程控制(SSC)模型，开发了短行程控制在线自学习功能。
For the short stroke control (SSC) model, the SSC online self-learning function was exploited.
在双足机器人跨越动态障碍物的在线控制问题中，脚步规划和步态控制的学习时间是关键问题。
In the question of on-line control for biped robot to step over dynamic obstacle, the learning time of footstep planning and gait pattern training is a crucial problem.
文中给出了神经网络的在线训练学习方法，并进行了船舶操纵控制仿真研究。
The on-line training methods for the neural networks in the control system are described, the simulation in ship maneuvering control …
文中给出了神经网络的在线训练学习方法，并进行了船舶操纵控制仿真研究。
The on-line training methods for the neural networks in the control system are described, the simulation in ship maneuvering control system is illustrated.
文中给出了神经网络的在线训练学习方法，并进行了船舶操纵控制仿真研究。
The on-line training methods for the neural networks in the control system are described, the simulation in ship maneuvering control system is illustrated.
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