Adaptive controller for multirotor based on estimated parameters

Abstract

This paper presents an innovative design of an adaptive control system for multirotors, unmanned aerial vehicles (UAVs) based on estimated parameters. A dynamic model of the UAV is derived by using the Newton–Euler method in terms of angular velocity. The derived model is then simplified into three separated-first-order linear differential equations, with coefficients derived from the combined effects of inertia, aerodynamic drag, gyroscopic effects, and angular rate, referred to as lumped parameters. To estimate those lumped parameters for designing controller, each simplified equation is restructured into a processing and measurement model. The states of these models are estimated by using the extended Kalman filter (EKF). A Proportional–Integral (PI) controller with control gains and dynamic and constant compensation, which are computed from the lumped parameters, is proposed to control the output of the simplified model. The entire multirotor controller is built and classified inner loop and outer loop as desired trajectory controller, altitude and thrust controller, attitude controller, adaptive angular velocity controller, and kinematics and dynamic controller. The proposed controller is simulated by using Matlab Simulink R2023b with circular and square trajectories with variable payload. The simulation results demonstrate that the proposed controller allows the multirotor to follow both desired paths successfully about 5 s. The steady-state error all axes in both paths is less than 0.02 meters. There is no significant fluctuation when UAV change payload and tracking direction. Moreover, the estimated parameters remain nearly constant at a steady state.