Research Initiation: Neural Network Robot Controller

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The principal investigator (PI) will study the use of artificial neural networks in robotic control. A variety of nonlinear adaptive control problems will be simulated for a one-link manipulator applying force to various objects. Flexible and rigid manipulators will interact with mobile and fixed objects to conduct various tasks specified by the PI The nonlinear adaptive controller will incorporate an artificial neural network that learns the nonlinear dynamics of the manipulator. Computer simulations will be used to assess the performance of robotic controllers based on neural networks. The ability of neural networks to approximate multivariate nonlinear functions representing robot manipulator dynamics will be exploited in a feedforward controller architecture. Research will focus on learning algorithms for neural networks used with both rigid and flexible one-link systems. Adaptation to varying dynamics caused by wear or by picking up objects will also be examined, as will alternative architectures for controller. the goal of this project is to create a neural network controller that is applicable to any control problem.