Using Toe-Off Impulse to Control Chaos in the Simplest Walking Model via Artificial Neural Network

Controlling chaos in a passive biped robot with an artificial neural network is investigated in this paper. The dynamical model is based on the compass-like biped robot proposed by Garcia et al. (1998) with a point-mass at the hip and infinitesimal point-masses at the feet ignoring the scuffing situation. The governing dynamics and chaotic behavior of the system is explored and the bifurcation diagram is drawn with respect to the ramp slope. Controlling chaos is based on stabilizing the unstable periodic orbits in the chaotic attractor. The UPOs are detected using an iterated algorithm. The artificial neural network is constructed using the information of seven previous steps and the control parameters in each one. The network is trained to find the appropriate control parameter in order to put the next step on the unstable periodic orbit. The control parameter is the toe-off impulse at the heel strike.

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