Constant Altitude Flight Control for Quadrotor UAVs with Dynamic Feedforward Compensation

Abstract

This study addresses the control problem of an unmanned aerial vehicle (UAV) during the transition period when the flying mode changes from hovering to translational motion in the horizontal plane. First, we introduce a compensation algorithm that improves height stabilization and reduces altitude drop. The main principle is to incorporate pitch and roll measurements into the feedforward term of the altitude controller to provide a larger thrust force. To further improve altitude control, we propose the fuzzy logic controller that improves system behavior. Simulation results presented in the paper highlight the effectiveness of the proposed controllers.

The Experimental Modeling of Quad-Rotor Actuators with Undefined Hardware Errors for Safety-Flight

“…The position of the quad-rotor is determined from the thrust T B and attitude of the quad-rotor from Equations 7, (8), and (9). In this case, thrust T B is determined by the thrust coefficient and the angular velocity of the propeller from Equations (3) and (4).…”

“…Because of the risk of a fast rotating actuator, the control of the quad-rotor is started with a simulation. The approach to controlling the motion of quad-rotor was developed using a variety of techniques, such as fuzzy logic [8], sliding-mode control [9], adaptive control [10], and robust control [11], among others. These control mechanisms assume the availability of a reliable mathematical model of the quad-rotor.…”

Altitude control of an Unmanned Aircraft System using a Super-Twisting controller based on High Order Sliding Mode Observer

“…In the literature we can find several works that deal with the quad-rotor's altitude control, including the simulation of an Adaptive Sliding Mode Controller [1], a PID controller [2], and a Fuzzy PD controller with a dynamic feedforward compensator [3]. In addition, experimental applications for altitude control of UASs have been reported, in [4] a Linear Quadratic Gaussian (LQG) controller is adopted in order to maintain a relatively constant altitude and a Kalman filter is designed to estimate the altitude velocity.…”

Vision Sensor-Based Human Tracking Control of a Quadcopter UAV with Position Uncertainty

“…Owing to the vertical mobility and hovering characteristics of small quadcopters, they are autonomous and able to fly indoors [1,2].…”