Abstract
This paper presents an alternative approach for the control and balancing operations of a simulated inverted pendulum. The proposed method uses a neuronal network called NeuraBase to learn the sensor events obtained via a simulated rotary encoder and a simulated stepper motor, which rotates the swinging arm. A neuron layer called the controller network will link the sensor neuron events to the motor neurons. The proposed NeuraBase network model (NNM) has demonstrated its ability to successfully control the balancing operation of the pendulum, in the absence of a dynamic model and theoretical control methods.
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Hercus, R., Wong, KY., Ho, KF. (2013). Balancing of a Simulated Inverted Pendulum Using the NeuraBase Network Model. In: Mladenov, V., Koprinkova-Hristova, P., Palm, G., Villa, A.E.P., Appollini, B., Kasabov, N. (eds) Artificial Neural Networks and Machine Learning – ICANN 2013. ICANN 2013. Lecture Notes in Computer Science, vol 8131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40728-4_66
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DOI: https://doi.org/10.1007/978-3-642-40728-4_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40727-7
Online ISBN: 978-3-642-40728-4
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