An Improved Model Free Adaptive Control Algorithm for the Wheeled Robot With Time Delay and Data Dropout

摘要

ABSTRACT In this work, an improved model‐free adaptive control algorithm combined with data compensation (IMFAC‐DC) is proposed for the attitude control of a two‐wheeled balancing vehicle with time delay and data dropout. First, the method introduces a dynamic linearization technique based on a pseudo partial derivative (PPD) with time‐varying parameter factors to dynamically linearize the dynamic process of the two‐wheeled balancing vehicle. Second, to address the existing time delay issue in the system, an improved model‐free adaptive controller is designed by proposing an adaptive factor coefficient and combining it with the Smith prediction method. Third, considering the presence of data dropout in practical systems, a novel data compensation mechanism is proposed to address this issue. The IMFAC‐DC algorithm utilizes only the input–output data of the controlled object to complete controller design. It combines the advantages of MFAC and the Smith predictor, and it exhibits good control performance for systems with time delay and data dropout. A series of experimental results based on an actual two‐wheeled balancing vehicle with time delay and data dropout are used to verify the effectiveness of the proposed method. A strict mathematical proof verifies the stability of the proposed method.