Figure 6.

Modulated Term impact at self-adaptive IO-DCN connection. Simulations were performed using plasticity mechanisms at PF-PC, MF-DCN, and PC-DCN synapses using a self-adaptive plasticity mechanism at IO-DCN connection for manipulating 2 kg external payload during 5000 trials. (A) Evolution of the average MAEs of the three robot joints during the learning process for a 2 kg payload with a cerebellum equipped with a self-adaptive synaptic weight IO-DCN connection. The modulating term plasticity at IO-DCN connection (see Equation 6) was ranged from base MTP/MTD values of 0.001 to 1000 respectively. The higher the values, the faster and the stabler the system converged. At values greater than 100 the system became unstable, a sort of windup effect appeared. The IO-DCN connection control command exceeded the physical limits of the robot-arm-system (it delivered a more corrective action at each integration step than the system could handle and needed). The IO-DCN connection control momentum was incapable of immediately responding to changes in the next-integration-step incoming error. (B) Normalized MAE convergences obtained during the learning process for a 2 kg payload when the modulating term plasticity at IO-DCN connection ranged from [0.001, 100].