A Feedback Error Learning (FEL) scheme was found to be applicable to joint angle control by Functional Electrical Stimulation (FES) in our previous study. However, the FEL-FES controller had a problem in learning of the inverse dynamics model (IDM) in some cases. In this paper, methods of applying the FEL to FES control were examined in controlling 1-DOF movement of the wrist joint stimulating 2 muscles through computer simulation under several control conditions with several subject models. The problems in applying FEL to FES controller were suggested to be in restricting stimulation intensity to positive values between the minimum and the maximum intensities and in the case of very small output values of the IDM. Learning of the IDM was greatly improved by considering the IDM output range with setting the minimum ANN output value in calculating ANN connection weight change.

This letter studies the tracking error in Multi-input Multi-output Feedback Error Learning (MIMO-FEL) system having insufficient excitation. It is shown that the error converges to zero exponentially even if the reference signal lacks the persistently excitation (PE) condition. Furthermore, by making full use of this fast convergence, we estimate the plant parameter while in operation based on frequency response. Simulation results show the effectiveness of the proposed method compared to a conventional approach.