Model‐free adaptive control method for a class of unknown MIMO systems with measurement noise and application to quadrotor aircraft
Shida Liu, Zhongsheng Hou, Xin Zhang, Honghai Ji
Abstract
In this work, a novel robust model‐free adaptive control (Ro‐MFAC) algorithm for a class of unknown multiple‐input multiple‐output (MIMO) systems with measurement noise is presented. The proposed algorithm, designing by a dynamic linearisation data model with the concept of the pseudo‐Jacobian matrix and an adaptive decreasing factor, is a pure a data‐driven control method, and only the input–output data are involved for the control system design. The introduction of the adaptive decreasing factor is to attenuate the noise effect on the performance for improving the robustness of the algorithm. The stability of the Ro‐MFAC proposed algorithm is proven by rigorous mathematical theory, and the effectiveness of the Ro‐MFAC is verified by a series of numerical simulations. Furthermore, the Ro‐MFAC is applied to an attitude adjustment problem of a practical quadrotor aircraft for demonstrating the applicability of the proposed approach.