Adaptive Hybrid Control Scheme for Controlling the Position of Coaxial Tri-rotor UAS

Masood, Rana Javed; Wang, Daobo; Ali, Zain Anwar; Anwar, Muhammad Ayaz

doi:10.31209/2018.100000009

Cited by 1 publication

(1 citation statement)

References 27 publications

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“…According to the demand of the controller, the vehicle tunes its dynamics. Te steady-state errors are diminished by the integral [21]. Te uncertainties guarantee the dynamics of the system as well as identical conditions, which are as follows:…”

Section: Controller Designingmentioning

confidence: 99%

Adaptive Control Algorithm for Trajectory Tracking of Underactuated Unmanned Surface Vehicle (UUSV)

Karnani

Raza

Asif

et al. 2023

Journal of Robotics

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The ability to track the trajectory or path on the sea surface remains a key measurement in the control system of an unmanned surface vehicle (USV). In this research, the designed algorithm defines the path and minimizes the disturbances to zero. Underactuated USVs are ships or boats, which operate on the water surface without a crew and the underactuated system has low actuators than its degree of freedom (DOF). The adaptive control strategy is applied to the unbounded system as the ocean due to its high performance, while the robust control system attains high performance in the bounded system. To consider the trajectory tracking of UUSV and provide an optimal control strategy for a ship in the presence of external disturbances, the study presents a controller-based on model reference adaptive control with an integrator (MRACI), which guarantees the stability of a closed-loop system. The vehicle experiences variations in the system response due to external disturbance. This abovementioned scheme reduces the variations to nearly equal to zero making the vehicle stable. First, use computer-based simulation to verify the proposed controller under two different scenarios. Then, simulation results show that the designed scheme lowers the errors and performs well.

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Section: Controller Designingmentioning

confidence: 99%