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 allow real-time estimation of joint torques and angular velocities from measurements of the angular positions. 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 joint torques estimation.