Bir Hava Robotu İçin Geliştirilen Genetik Ayarlı LQR Kontrolörün Performansının Değerlendirilmesi

Year 2024, Volume: 6 Issue: 3

Ali Tahir Karaşahin

Abstract

Hava robotları erişebilir, basit ve üstün kabiliyetlerinden dolayı birçok uygulama alanında geniş yer bulmaktadır. Geniş bir yelpazede kullanılan hava robotlarından farklı beklentiler istenmektedir. Uygulama alanlarına özel oluşan bu beklentilere cevap verebilmek için hava robotlarında kullanılan geleneksel kontrolör tasarımlarında birtakım değişikliklere gidilmesi gerekmektedir. Bu çalışmada bir hava robotunun yörünge takibi için genetik ayarlı ve integral etkisine göre çalışan doğrusal karesel regülatör (LQR) kontrolörü geliştirilmiştir. Bu kontrolörün performansını karşılaştırmak için LQR ve bulanık oransal-integral-türevsel (FPID) kullanılmıştır. Geliştirilen ve kullanılan kontrolörler model-tabanlı ve hibrit kontrolörler olarak ifade edilmektedir. Hava robotu olarak Parrot AR. Drone 2.0. kullanılmıştır. Belirtilen hava robotu MATLAB/Simulink ortamında 6 serbestlik derecesi (DOF) ile modellenmiştir. Geliştirilen kontrolörlerin performansları sekiz eğrisinin referans olarak takip edilmesi esnasında oluşan hata değerine göre değerlendirilmiştir. Hata değerleri ortalama kare hata karekökü (RMSE) kriterine göre incelenmiştir. Elde edilen sonuçlara göre standart LQR kontrolör en yüksek RMSE hata değerini üretmiştir. Genetik ayarlı ve integral etkisine göre tasarlanan LQR kontrolör, standart LQR kontrolöre göre %43,22 FPID kontrolörüne göre %22,99 oranında daha başarılı sonuçlar elde etmiştir. MATLAB/Simulink ortamında gerçekleştirilen simülasyon sonuçlarına göre sekiz eğrisi yörünge takibinde genetik ayarlı LQR kontrolörü daha başarılı sonuçlar elde ettiği gözlemlenmiştir.

Keywords

Hava robotu, LQR kontrolör, Genetik algoritma, Bulanık PID, Yörünge takibi

Performance Evaluation of a Genetically Tuned LQR Controller for an Aerial Robot

Abstract

Aerial robots are widely used in many application areas due to their accessibility, simplicity and superior capabilities. Different expectations are required from aerial robots used in a wide range of applications. In order to meet these application-specific expectations, it is necessary to make some changes in the traditional controller designs used in aerial robots. In this study, a linear quadratic regulator (LQR) controller with genetic tuning and integral effect is developed for trajectory tracking of an aerial robot. LQR and fuzzy proportional-integral-derivative (FPID) are used to compare the performance of this controller. The developed and used controllers are referred to as model-based and hybrid controllers. Parrot AR. Drone 2.0. is used as an aerial robot. The aerial robot is modeled in MATLAB/Simulink environment with 6 degrees of freedom (DOF). The performances of the developed controllers are evaluated according to the error value during the tracking of the eight curve as a reference. The error values are analyzed according to the root mean square error (RMSE) criterion. According to the results obtained, the standard LQR controller produced the highest RMSE error value. The LQR controller designed according to genetic tuning and integral effect obtained 43.22% better results than the standard LQR controller and 22.99% better results than the FPID controller. According to the simulation results in MATLAB/Simulink environment, it is observed that the genetically tuned LQR controller achieves better results in eight curve trajectory tracking.

Keywords

Aerial Robot, LQR Controller, Genetic Algorithm, Fuzzy PID, Trajectory Tracking

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