Abstract
A synthesis of a sliding mode control law, for a robot arm, based on the robot model with a positive definite inertia matrix, identified with an artificial neural network, is presented. The structure of the neural network resemble a Lagrange-Euler mathematical model of the robot, and identifies the positive definite inertia matrix. A design of the neural model is based on the Cholesky decomposition of the identified inertia matrix.
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Możaryn, J., Kurek, J.E. (2010). Sliding Mode Control of Robot Based on Neural Network Model with Positive Definite Inertia Matrix. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15822-3_34
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DOI: https://doi.org/10.1007/978-3-642-15822-3_34
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