Minimum variance adaptive control method for blind guide

Accurately inducing the blind to track a given path is an important basis and premise of wearable blind guide systems. In order to achieve safe travel for the blind, the walking dynamics model of the blind and an adaptive control algorithm were studied. For different users in the actual walking process, the model parameters change due to psychological and physiological differences and interactions with the environment, and thus an adaptive controller is required. An induction method based on minimum variance self-tuning control algorithm was proposed. Firstly, the parameters of the controlled object were estimated by the extended least squares. Then the Diophantine equation was solved to obtain the controller parameters. Finally, the output of the controller was obtained by the minimum variance control algorithm. The simulation results show that the minimum variance self-tuning control algorithm can track the circular trajectory well after identifying the model parameters, and the average travel-trajectory error range of experimental tests is (-0.5957m, 0.4811m), which verifies the accuracy and adaptability of the proposed method.