Abstract
This work designed a disturbance-observer-based nonlinear sliding mode surface controller (SMC) and validated the controller using a simulated PX4-conducted quadcopter. To achieve this goal, this research (1) developed a dynamic mathematical model; (2) built a PX4-based simulated UAV following the model-based design process; (3) developed appropriate sliding mode control laws for each degree of freedom; (4) implemented disturbance observers on the proposed SMC controller to achieve finer disturbance rejection such as crosswind effect and other mutational disturbances; (5) optimized the SMC controller’s parameters based on particle swarm optimization (PSO) method; and (6) evaluated and compared the quadcopter’s tracking performance under a range of noise and disturbances. Comparisons of PID control strategies against the SMC were documented under the same conditions. Consequently, the SMC controller with disturbance observer facilitates accurate and fast UAV adaptation in uncertain dynamic environments.
Subject
Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering
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