Robust Feedback Linearization Control Design for Five-Link Human Biped Robot with Multi-Performances

The study first proposes the difficult nonlinear convergent radius and convergent rate formulas and the complete derivations of a mathematical model for the nonlinear five-link human biped robot (FLHBR) system which has been a challenge for engineers in recent decades. The proposed theorem simultaneously has very distinctive superior advantages including the stringent almost disturbance decoupling feature that addresses the major deficiencies of the traditional singular perturbation approach without annoying complete conditions for the discriminant function and the global exponential stability feature without solving the impractical Hamilton-Jacobi equation for the traditional H-infinity technique. This article applies the feedback linearization technique to globally stabilize the FLHBR system that greatly improved those shortcomings of nonlinear function approximator and make the effective working range be global for whole state space, whereas the traditional Jacobian linearization technique is valid only for areas near the equilibrium point. In order to make some comparisons with traditional approaches, first example of the representative ones, that cannot be addressed well for the pioneer paper, is shown to demonstrate the fact that the effectiveness of the proposed main theorem is better than the traditional singular perturbation technique. Finally, we execute a second simulation example to compare the proposed approach with the traditional PID approach. The simulation results show that the transient behaviors of the proposed approach including the peak time, the rise time, the settling time and the maximum overshoot specifications are better than the traditional PID approach.

Automated summary

The study proposes difficult nonlinear convergent radius and convergent rate formulas and derives a mathematical model for the nonlinear five-link human biped robot (FLHBR) system. The feedback linearization technique is applied to globally stabilize the FLHBR system, addressing the shortcomings of nonlinear function approximator and expanding its effective working range.