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

فایل این مقاله در 7 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

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.

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