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机器人控制的仿真，使用遗传算法优化神经网络-control of the robot simulation, the use of genetic algorithm optimization neural network
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提出了一种新颖的控制方案，即采用神经网络预测控制器来控制机器人的力／位置．这种控
制器能任意逼近机器人这种不确定对象，不用知道系统的精确结构，同时由于预测控制的加入，使系
统在线计算方便，控制质量提高了-A novel control scheme, namely, the use of neural network predictive controller to control the robot s force/position. This control
Syste
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用神经网络加遗传算法写的模拟控制机器人行走的程序-Genetic algorithm neural network increases with written procedures for analog control walking robot
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基于改进BP 神经网络的移动机器人寻线控制神经网络系统具有自学习和自适应的能力，同时有很强的容错性和鲁棒性，适用于处理难于语言化的模式信息。为使移动机器人沿地面标志线自主运动，采用CCD 图像传感器与PC/104总线相结合的硬件系统，运用神经网络的模式识别功能，实现了机器人的寻线控制，实验结果表明该方法是可行的，能有效地提高移动机器人对环境的适应性和其智能化水平。- Neural Network has the ability of self-learning and self-adaptati
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飞行机器人递归小脑神经网络模型分解控制Flying robot recursive CMAC neural network model decomposition control-Flying robot recursive CMAC neural network model decomposition control
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模糊神经网络控制的英文论文，主要要用于机器人跟踪控制问题可直接使用。
-Fuzzy Neural Network Control of the English papers, mainly used for tracking control of robot complete source code can be used directly.
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神经网络机器人避障matlan仿真程序可模拟机器器人在空间的避障动作 ，经测试可直接使用。
-The neural network robot obstacle avoidance matlan simulation program can simulate the machine control space to avoid this obstacle has been tested and can be used directly.
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《机器人控制系统设计与matlab仿真》第三章“机器人神经网络自适应控制”源代码-" Robot control system design and the matlab simulation" " robot neural network adaptive control source code
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本文采用RBF神经网络控制对双杆机器人进行参数辨识得到其控制模型后，采用PD控制机器人。-In this paper, the RBF neural network to identify the parameters to get the control model of the double-pole robot control, PD control the robot.
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Design a feedforward network is u
dehaze algorithms review
path planning using GA and ACO...
The neural network adaboost stron
TS neural network m files, fast c
bp neural network, written with C
Bayes net and memory based learni
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Design a feedforward network is u
dehaze algorithms review
path planning using GA and ACO...
The neural network adaboost stron
TS neural network m files, fast c
bp neural network, written with C
Bayes net and memory based learni
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基于神经网络观测器的单关节机械手反演控制。将估计速度代替实际速度，可实现无需实际速度信号检测的控制-Single-joint robot based on neural network observer inversion control. Instead of the actual speed of the estimated velocity can be achieved without the control of the actual speed signal detection
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In this paper, an orthogonal functions neural network is used to
achieve the control of nonlinear systems. The adaptive controller is constructed
by using Chebyshev orthogonal polynomials neural network, which has advantages
such as simple stru
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双力臂机械手控制基于不确定补偿神经网络自适应控制-Dual-arm robot control based on uncertain compensation Neural Network Adaptive Control
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单力臂机械手控制基于模型分块的机器人神经网络自适应控制-Single-arm robot control block of model-based neural network adaptive control robot
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双力臂机械手控制，基于分块模型逼近的机器人神经网络自适应控制-Dual-arm robot control, block model approach based on neural network adaptive robot control
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工作空间机械手的神经网络自适应控制程序 加入神经网络智能算法 可以很好地逼近模型实例 -Workspace robot neural network adaptive neural network control program added intelligent algorithm can approximate model instance
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机器人系统的控制方法，利用滑模控制和神经网络来实现。-Robot system control method, using sliding mode control and neural network to achieve.
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在Matalb中进行机器人控制仿真程序——机器人神经网络自适应控制(Robot neural network adaptive control in Matlab)
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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of t
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