A Model Predictive Based Controller Design for a Class of Aerial Vehicle’s Trajectory Tracking Problem; In The Presence of Calculation’s Restrictive Assumptions
سال انتشار: 1401
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 216
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شناسه ملی سند علمی:
METEC06_021
تاریخ نمایه سازی: 26 بهمن 1401
چکیده مقاله:
In the present paper, a class of dynamical systems for unmanned aerial vehicles (UAV) is illustrated and
the position and attitude tracking control problem are proposed for the noted dynamics system. Nevertheless,
the UAV dynamics system is considered as an underactuated system since the number of control command
signals are lower than the outputs of the system. Consequently, the noted issue is the main challenge in the
aforementioned control configuration. As a regard, a predictive-based, optimal controller is proposed for the
system and the linear model predictive control architecture is examined in order to overcome the problem’s
challenge due to the under actuation of the system and to achieve the tracking performance in an acceptable
manner. Moreover, the UAV dynamics system is considered as a highly coupled and generally unstable system.
in this regard, the control architecture should stabilize the open-loop dynamics system, satisfactorily. At last,
the computational complexity of the online, optimal MPC controller is considered an important factor in
practical and experimental issues. Thus, a computational complexity criterion is proposed for the control
architecture in this paper, based on the number of iterations of the optimization algorithm in each time step.
Conclusively, the controller performance and UAV dynamics system are examined in the simulation
environment and the advantages and the capability of the controller and closed-loop system is illustrated by
numerical results.
کلیدواژه ها:
Unmanned Aerial Vehicle (UAV) ، Underactuated Dynamics System ، Model Predictive Control
(MPC) ، Online Controller ، Iterative Optimization
نویسندگان
Zahra Jafari Shahbazzadeh
PhD candidate, School of Mechanical Engineering, Shiraz University
Erfan Nejabat
Ph.D. candidate, Department of Mechatronic Engineering, K. N. Toosi University of Technology