Fuzzy neural networks quadratic stabilization output feedback control for biped robots via H∞ approach

A novel fuzzy neural networks (FNN) quadratic stabilization output feedback control scheme is proposed for the trajectory tracking problems of biped robots with an FNN nonlinear observer. First, a robust quadratic stabilization FNN nonlinear observer is presented to estimate the joint velocities of a biped robot, in Which H. approach and variable structure control (VSC) are embedded to attenuate the effect of external disturbances and parametric uncertainties. After the construction of the FNN nonlinear observer, a quadratic stabilization FNN controller is developed with robust hybrid control scheme. As the employment of quadratic stability approach, not only it afford the possibility to trade off the design between FNN, H-infinity optimal control, and VSC, but also the conservative estimation of FNN reconstruction error bound is avoided by considering the system matrices uncertainties separately. It is shown that all the signals in the close-loop control system are bounded.