An Underactuated Control System Design for Adaptive Autopilot of Fixed-Wing Drones

Abstract

Effective design of autopilots for fixed-wing unmanned aerial vehicles (UAVs) is still a great challenge, due to unmodeled effects and uncertainties that these vehicles exhibit during flight. Unmodeled effects and uncertainties comprise longitudinal/lateral cross-couplings, as well as poor knowledge of equilibrium points (trimming points) of the UAV dynamics. The main contribution of this article is a new adaptive autopilot design, based on uncertain Euler-Lagrange dynamics of the UAV and where the control can explicitly take into account under-actuation in the dynamics, reduced structural knowledge of cross-couplings and trimming points. This system uncertainty is handled via appropriately designed adaptive laws: stability of the controlled UAV is analyzed. Hardware-in-the-loop tests, comparisons with an Ardupilot autopilot and with a robustified autopilot validate the effectiveness of the control design, even in the presence of strong saturation of the UAV actuators.

Embedding Adaptive Features in the ArduPilot Control Architecture for Unmanned Aerial Vehicles

“…At the same time, researchers proposed their own autopilot architectures, either based on model predictive control [27], underactuated Euler-Lagrange dynamics [28] or deep reinforcement learning [29], among others. These autopilots require completely different architectures, which cannot operate along with the original off-the-shelf architecture.…”

Nonsingular predefined‐time dynamic surface control of a flexible‐joint space robot with actuator constraints

“…4 However, the flexible-joint robot arm is essentially an underactuated Euler-Lagrange system, which greatly increases the difficulty of controller design and affects the ability to achieve high-precision control. [5][6][7] Moreover, the coupling between the robotic arms and the satellite base makes the movement of space robots susceptible to sustained vibration of the satellite base and the end-effectors, which poses further challenges to the accurate control of flexible-joint space robots. 8,9 Meanwhile, considering that a wide variety of tasks may place a wide variety of demands on the error convergence time of a space robot, it is also a worthwhile problem to investigate how the settling time can be directly set to meet the task demands.…”

“…Compared with the traditional rigid robot arm, the robot arm equipped with harmonic reducers, that is, the flexible‐joint robot arm, improves the performance of the robot arm 4 . However, the flexible‐joint robot arm is essentially an underactuated Euler–Lagrange system, which greatly increases the difficulty of controller design and affects the ability to achieve high‐precision control 5–7 . Moreover, the coupling between the robotic arms and the satellite base makes the movement of space robots susceptible to sustained vibration of the satellite base and the end‐effectors, which poses further challenges to the accurate control of flexible‐joint space robots 8,9 .…”

A Chip-Level Testing Platform of Unmanned Vehicle Autopilot Systems with FPGA-Based Hardware-in-the-Loop Simulation

“…As unmanned vehicles such as quadcopters [1,2], fixed-wing [3], unmanned ground vehicles [4], and unmanned surface ships [5] are widely used in various fields, the electromechanical equipment of these unmanned vehicles is becoming increasingly complex, and the tasks they undertake are becoming more and more diverse. However, intensive flight missions may induce fault that can lead to conflicts, collisions, and crashes.…”