An alternative to inverse dynamics joint torques estimation in human stance based on a Takagi-Sugeno unknown inputs observer in the descriptor form

An alternative to inverse-dynamics joint-torques estimation in human stance is proposed. This alternative is based on unknown-input observers which, from measurements of the angular positions, allow real-time estimation of joint torques and angular velocities. To design the aforementioned observer, a nonlinear state-space dynamical descriptor model is proposed. The descriptor model is then written into the form of a Takagi-Sugeno (T-S) model, from which a T-S observer in the descriptor form is designed. Then, convergence of the estimation errors (in position, velocities and torques) is established using a quadratic Lyapunov function through LMI conditions. Finally, the proposed approach is successfully compared with commonly used inverse-dynamics jointtorques estimation.