article · PLoS ONE
A new control method has been developed to improve trajectory tracking for quadrotor unmanned aerial vehicles operating under external disturbances and uncertainty. Using the Newton-Quaternion formalism, a singularity-free dynamic model of the quadrotor was established. The control system applies a super twisting algorithm to reduce chattering, while Particle Swarm Optimisation tunes the controller gains. To handle situations where disturbance boundaries are unknown, the system incorporates an adaptive rule based on Lyapunov stability to ensure robust control. In simulation tests, this controller lowered tracking errors to 0.1% for roll, 0.05% for pitch, and 2.2% for altitude. It also rejected external disturbances effectively, yielding minimal steady-state errors of 0.01 degrees for roll, 0.02 degrees for pitch, and 0.001 degrees for yaw. These outcomes show improved performance over conventional controllers and indicate potential feasibility for real-time flight implementation.
Unmanned aerial vehicles often struggle with flight stability and path precision when facing unexpected environmental disturbances like wind gusts. By suppressing erratic control vibrations and adjusting automatically to unknown disturbances, this controller helps drones follow intended flight paths far more accurately. Such stability improvements are vital for preventing crashes and ensuring reliable automated flight performance.
This control technology is relevant to drone manufacturers and developers of flight control software seeking improved stability under turbulent conditions. Currently validated only through computer simulations, the work represents early-stage applied research that remains short of physical flight testing. However, the simulation results suggest that real-time implementation on physical quadrotor unmanned aerial vehicles is feasible.
AI-generated from the published abstract. Always read the original work before citing.
This paper presents an improved nonsingular adaptive super twisting sliding mode control for tracking of a quadrotor system in the presence of external disturbances and uncertainty. The initial step involves developing a dynamic model for the quadrotor that is free from singularities, achieved through the utilization of the Newton-Quaternion formalism. Then, the super twisting algorithm is used to develop a novel sliding mode control that mitigates chattering. Particle Swarm Optimization (PSO) is employed for the adjustment of the controller gains. Moreover, to maintain stable control of the quadcopter, even in scenarios where the upper limit of disturbances is unknown, an adaptive rule grounded in Lyapunov stability is applied. Simulation results demonstrate that the proposed controller reduces tracking errors to 0.1% for roll, 0.05% for pitch, and 2.2% for altitude, outperforming other state-of-the-art sliding mode controllers. Additionally, the proposed controller effectively rejects disturbances, maintaining minimal steady-state errors of 0.01° for roll, 0.02° for pitch, and 0.001° for yaw, significantly better than conventional controllers. These results highlight tracking and disturbance rejection capabilities of the proposed controller, making its real-time implementation for quadrotor Unmanned Aerial Vehicles (UAVs) feasible.
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DOI: 10.1371/journal.pone.0309098
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