Motor Maps for Nonlinear Control

Statistics – Applications

Scientific paper

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Adaptive Control, Chaos, Control Systems Design, Control Theory, Neural Nets, Neurophysiology, Nonlinear Systems, Self Adaptive Control Systems, Transformations (Mathematics), Control Of Chaos, Applications Of Chaos, Neuroscience

Scientific paper

In this paper the design of a motor map to control a chaotic system is presented. A feedback entrainment scheme is adopted: a system with different parameters is used to generate the reference trajectory for the chaotic system to be controlled, while the motor map provides the appropriate gain value of the feedback signal. As input of the motor map the state of the system to be controlled is considered. The motor map based adaptive controller offers high performances, specially in the case when the reference trajectory is switched into another one. In this case, a specialization of the neurons constituting the motor map is observed: while a group of neurons learns the appropriate control law for a reference trajectory, another group specializes itself to control the system when the other trajectory is used as reference. Moreover, a discrete components hardware implementation of the motor map has been realized.

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