Model Reference Adaptive Impedance Control Method Based on Online Environment Stiffness Identification

A force control method combining model reference adaptive control and impedance control is studied for the work environment of physical interaction with unknown and time-varying environmental stiffness. The updating law of adaptive gains is derived to improve the applicability of the system to different environments. The uncertainty is compensated by a radial basis function neural network. The variable forgetting factor recursive least squares method is used to identify the environmental stiffness, optimize the controller output with the identification results, and reduce the force response overshoot. The stability of the system is proved by means of the Lyapunov stability theorem. Finally, the effectiveness of the proposed algorithm is verified by simulation results.