Distributed fault tolerant model predictive control for multi‐unmanned aerial vehicle system

2021 ◽  
Author(s):  
Boyang Zhang ◽  
Xiuxia Sun ◽  
Shuguang Liu ◽  
Xiongfeng Deng
Keyword(s):  
Model Predictive Control ◽  
Unmanned Aerial Vehicle ◽  
Predictive Control ◽  
Fault Tolerant ◽  
Vehicle System ◽  
Aerial Vehicle

scholarly journals Nonlinear Model Predictive Control for the Stabilization of a Wheeled Unmanned Aerial Vehicle on a Pipe

2019 ◽  
Vol 4 (4) ◽  
pp. 4314-4321
Author(s):  
Suping Zhao ◽  
Fabio Ruggiero ◽  
Giuseppe Andrea Fontanelli ◽  
Vincenzo Lippiello ◽  
Zhanxia Zhu ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Unmanned Aerial Vehicle ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Nonlinear Model Predictive Control ◽  
Aerial Vehicle

Tracking control of multiple unmanned aerial vehicles incorporating disturbance observer and model predictive approach

2019 ◽  
Vol 42 (5) ◽  
pp. 951-964 ◽  
Author(s):  
Boyang Zhang ◽  
Xiuxia Sun ◽  
Shuguang Liu ◽  
Xiongfeng Deng
Keyword(s):  
Model Predictive Control ◽  
Unmanned Aerial Vehicle ◽  
Predictive Control ◽  
Disturbance Observer ◽  
Control Method ◽  
Differential Evolution Algorithm ◽  
Reference Trajectory ◽  
Control Approach ◽  
Unknown Disturbances ◽  
Aerial Vehicle

This paper studies the disturbance observer-based model predictive control approach to deal with the unmanned aerial vehicle formation flight with unknown disturbances. The distributed control problem for a class of multiple unmanned aerial vehicle systems with reference trajectory tracking and disturbance rejection is formulated. Firstly, a local distributed controller is designed by using the model predictive control method to achieve stable tracking, where the local optimization problem is solved by an adaptive differential evolution algorithm. Then, a feedforward compensation controller is introduced by using a disturbance observer to estimate and compensate disturbances, and improve the ability of anti-interference. Besides, the stability of the proposed composite controller is analyzed as well. Finally, the simulation examples are provided to illustrate the validity of proposed control structure.

Application of Model Predictive Control to Position and Height Limitation of a Quadrotor Unmanned Aerial Vehicle

2015 ◽  
Author(s):  
Yiqun Dong ◽  
Zhixiang Liu ◽  
Bin Yu ◽  
Youmin Zhang
Keyword(s):  
Model Predictive Control ◽  
Unmanned Aerial Vehicle ◽  
Predictive Control ◽  
Experimental Tests ◽  
Optimization Approach ◽  
Laguerre Function ◽  
Aerial Vehicle ◽  
On Line ◽  
Vehicle Position ◽  
Recursive Optimization

This paper discusses a position and height limitation control for a quadrotor UAV (Unmanned Aerial Vehicle) using Model Predictive Control (MPC) approach. Nonlinear dynamics of the quadrotor is discussed first, and decoupled linearized dynamics is obtained. For the implementation of MPC, extended state vector of vehicle is generated, and augmented linear dynamics is constructed. The MPC in this paper utilizes a set of Laguerre function as basis to approximate the future movement of modeled vehicle. Position/height constraints and vehicle actuator characteristics enter the dynamics as linearized inequalities, which could be solved on-line via a recursive optimization approach. While validations based on experimental tests will be conducted in future, currently simulations have been completed. Based on the simulation results, when state of the vehicle is laid within the permissible bound, it retains the same dynamics of original vehicle. However, if predicted response exceeds the limits, however, MPC will take effect and restrict associate vehicle states. The discussed MPC framework in this paper is considered to be applicable.

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