Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A neural net (NN) controller for a general serial-link robot arm is developed. The NN has two layers so that linearity in the parameters holds, but the "net functional reconstruction error" is taken as nonzero. The structure of the NN controller is derived using a filtered error/passivity approach. It is shown that standard backpropagation, when used for real time closed-loop control, can yield unbounded NN ights if (1) the net cannot exactly reconstruct a certain required control function, or (2) there are bounded unknown disturbances in the robot dynamics. An online ight tuning algorithm including a correction term to backpropagation guarantees tracking as ll as bounded ights. The notions of a passive NN and a robust NN are introduced. >
['F. L. Lewis', 'Liu K', 'A. Yesildirek']
I am writing a research paper on a idea Neural net robot controller with guaranteed tracking performance
[{"from": "human", "value": "I am writing a research paper on a idea Neural net robot controller with guaranteed tracking performance"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A neural net (NN) controller for a general serial-link robot arm is developed. The NN has two layers so that linearity in the parameters holds, but the \"net functional reconstruction error\" is taken as nonzero. The structure of the NN controller is derived using a filtered error/passivity approach. It is shown that standard backpropagation, when used for real time closed-loop control, can yield unbounded NN ights if (1) the net cannot exactly reconstruct a certain required control function, or (2) there are bounded unknown disturbances in the robot dynamics. An online ight tuning algorithm including a correction term to backpropagation guarantees tracking as ll as bounded ights. The notions of a passive NN and a robust NN are introduced. >"}]