Adaptive learning with large variability of teaching signals for neural networks and its application to motion control of an industrial robot

Mathematics

• Adaptive Learning 94%
• Back-propagation Algorithm 23%
• Centrifugal Force 44%
• Coefficient 7%
• Compensator 71%
• Controller 54%
• Coriolis Force 41%
• Derivative 8%
• Directly proportional 12%
• Dynamic Model 15%
• Feedforward 56%
• Friction 14%
• Gravity 30%
• Industrial Robot 100%
• Learning 38%
• Learning Process 19%
• Manipulator 36%
• Motion Control 90%
• Neural Networks 53%
• Performance 8%
• Recurrent Neural Networks 18%
• Requirements 11%
• Robotics 17%
• Simulation 8%
• Teaching 58%
• Trial and error 19%
• Tuning 16%

Engineering & Materials Science

• Backpropagation 13%
• Controllers 30%
• Derivatives 11%
• Dynamic models 11%
• Friction 9%
• Gravitation 25%
• Industrial robots 63%
• Manipulators 24%
• Motion control 58%
• Neural networks 34%
• Recurrent neural networks 14%
• Robotics 10%
• Sampling 9%
• Teaching 50%
• Tuning 11%