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The authors present a scheme for intelligent control of robotic manipulators. This is a hybrid system of neuromorphic control and symbolic control of a robotic manipulator, including a neural network for the servo control and a knowledge-based approximation. The neural network in the servo control level is for numerical manipulation, while the knowledge-based approximation is for symbolic manipulation. In neuromorphic control, the neural network compensates for the nonlinearity of the system and the uncertainty in the environment. The knowledge base develops the control strategy symbolically for the servo level. This is an analogous control system to the human cerebral control structure.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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Shibata et al. (2003) studied this question.
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