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An improved nonsingular adaptive super twisting sliding mode controller for quadcopter
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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.
Public Library of Science (PLoS)
Title: An improved nonsingular adaptive super twisting sliding mode controller for quadcopter
Description:
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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