An adaptive composite disturbance rejection for attitude control of the agricultural quadrotor UAV

Author(s):  
Shubo Wang ◽  
Jian Chen ◽  
Xiongkui He
Author(s):  
Jameson Y. Lee ◽  
Zachary Cook ◽  
Alexander Barzilov ◽  
Woosoon Yim

Multirotor Unmanned Aerial Systems (UAS) are highly mobile in flight and possess stable hovering capabilities. Because of their unique flight characteristics, the utilization of the platform for active tasks such as aerial manipulation is highly attractive. Much work has been done in recent years towards the implementation of multirotor for aerial manipulation, however, progress in the field has been slow due to the many challenges involved in the implementation of robust rotor control. In an attempt to reduce the effects of the manipulator, a technique for disturbance rejection using a novel balancing mechanism is proposed. In this paper, the dynamic equations of a coupled multirotor and manipulator are analyzed as a single body for use in the attitude control of the platform. By mounting the mechanism, the platform effectively gains marginal control over the positioning of its center of gravity relative to a body fixed frame. It can be shown that the increased mobility can be utilized to reduce rotor saturation for any given flight condition and improve the effectiveness of previously developed rotor control methods.


2011 ◽  
Vol 383-390 ◽  
pp. 358-365 ◽  
Author(s):  
Fu Lin Teng ◽  
Hong Yu Ge ◽  
Hong Sheng Li ◽  
Jian Hua Zhang

Modern spacecraft demands from an attitude control system very high performance and accuracy, and many new features, such as disturbance rejection capability. The recently developed active disturbance rejection control technology is applied to the attitude control of spacecraft subject to disturbances and parametric uncertainties. Simulation and experiment show significant advantages of the proposed attitude controller over the controller resulting from conventional PID approach.


2020 ◽  
Vol 10 (11) ◽  
pp. 3719
Author(s):  
Ran Jiao ◽  
Wusheng Chou ◽  
Yongfeng Rong ◽  
Mingjie Dong

Aerial operation with unmanned aerial vehicle (UAV) manipulator is a promising field for future applications. However, the quadrotor UAV manipulator usually suffers from several disturbances, such as external wind and model uncertainties, when conducting aerial tasks, which will seriously influence the stability of the whole system. In this paper, we address the problem of high-precision attitude control for quadrotor manipulator which is equipped with a 2-degree-of-freedom (DOF) robotic arm under disturbances. We propose a new sliding-mode extended state observer (SMESO) to estimate the lumped disturbance and build a backstepping attitude controller to attenuate its influence. First, we use the saturation function to replace discontinuous sign function of traditional SMESO to alleviate the estimation chattering problem. Second, by innovatively introducing super-twisting algorithm and fuzzy logic rules used for adaptively updating the observer switching gains, the fuzzy adaptive saturation super-twisting extended state observer (FASTESO) is constructed. Finally, in order to further reduce the impact of sensor noise, we invite a tracking differentiator (TD) incorporated into FASTESO. The proposed control approach is validated with effectiveness in several simulations and experiments in which we try to fly UAV under varied external disturbances.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Bo Wang ◽  
Wei Liu ◽  
Zhongtao Cheng ◽  
Lei Liu ◽  
Yongji Wang

This paper designs a double-loop cascade active disturbance rejection control (ADRC) to overcome the external disturbances and parameter uncertainty during hypersonic vehicle flight. The vehicle attitude angle and attitude angular velocity are regulated in outer loop and inner loop, respectively. A stochastic robust approach is employed to further tune the ADRC parameters for better control performances. The Monte Carlo sampling of uncertain parameter is adopted to evaluate the stochastic robust performance. An improved differential evolution algorithm that combines neighborhood field optimization and triangular mutation is employed as the numerical solver. Simulation results show that the ADRC controller with optimized parameters manifests improved robustness as well as good control performances.


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