Model Predictive Control (MPC) for Quadcopter UAV Dynamics: A Technical Overview of Obstacle Avoidance

Zihao Zhou

doi:10.6919/ICJE.202508_11(8).0013

Authors

Zihao Zhou

DOI:

https://doi.org/10.6919/ICJE.202508_11(8).0013

Keywords:

Quadrotor UAV; Model Predictive Control; Dynamic Obstacle Avoidance; Nonlinear Control Method; Machine Learning; Real-Time Performance and Safety.

Abstract

With the continuous progress of UAV technology and the increasingly wide range of application scenarios, quadrotor UAVs have shown great potential in the fields of logistics and distribution, agricultural inspection, and emergency rescue. However, in these application scenarios, UAVs face complex and changing environmental challenges, such as high-rise buildings in cities, irregular terrain in agricultural areas, and uncertainties in disaster sites. These challenges require UAVs to have high-precision path tracking capabilities and dynamic obstacle avoidance to ensure that they can accomplish their tasks safely and efficiently. Meanwhile, Model Predictive Control (MPC), as an advanced control strategy, has received more and more attention due to its ability to deal with constraints and optimize predictions. MPC is well suited to deal with UAV navigation problems in complex dynamic environments by predicting the future state using system models and formulating optimal control decisions based on these predictions. navigation problems in complex dynamic environments. Although MPC theoretically offers the possibility of solving the above problems, research in practical applications, especially in dynamic obstacle avoidance, is still in the developmental stage, and there are many under-explored technical difficulties, such as how to improve the efficiency of the obstacle avoidance algorithm and the robustness of the system under the premise of guaranteeing real-time performance. Therefore, this topic originates from the combination of the practical needs of dynamic path tracking for UAVs and the theoretical development of MPC, aiming to find out the issues that have not been explored or controversial on the basis of combing the existing researches through the technical overview of dynamic obstacle avoidance for MPC quadcopter UAVs, and provide the direction for the subsequent related researches. In addition, through in-depth research in this field, this project also hopes to promote the development of intelligent control systems and provide new ideas and solutions for future automation and intelligent technologies.

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