Bir SCARA Robot Manipülatörün Konum Kontrolü için SMC Denetleyici Parametrelerini Belirlemeye Yönelik Arı Algoritması Yaklaşımı

Öz

Bu çalışmada, SCARA tip bir robot manipülatörün konum kontrolü, Arı algoritması kullanılarak parametre optimizasyonuna dayanan kayan kipli kontrol (SMC) yöntemi kullanılarak incelenmiştir. SCARA manipülatörün modellenmesi MSC Adams'ta yapılmış ve kontrol uygulaması MATLAB yazılımında gerçekleştirilmiştir. SCARA manipülatörün sayısal modeli, MSC Adams yazılımı üzerinde sanal bir prototip kurularak elde edilmiştir. Ayrıca, oluşturulan sanal prototipin doğruluğunu kontrol etmek için SCARA manipülatörün ters kinematik denklemleri Matlab/Simulink yazılımı kullanılarak oluşturulmuştur. Ek olarak, daha iyi sonuçlar elde etmek için SMC kontrolcünün parametreleri Arı Algoritması ile optimize edilmiştir. Ardından MSC Adams-MATLAB eş zamanlı simülasyonu kullanılarak sanal prototip üzerinde sistemin kontrolcü performansı incelenmiştir. Ayrıca, parametre optimizasyonu için bir başka meta-sezgisel yöntem olan Genetik Algoritma kullanılmış ve elde edilen sonuçlar ile Arı Algoritmasının performansı karşılaştırılmıştır. Sonuç olarak, Arı Algoritmasının robotik sistemlerin kontrolü ile ilgili çalışmalarda kullanılabilir olduğu gözlemlenmiştir.

Anahtar Kelimeler

• Arı algoritması
• Kayan kipli kontrol
• Optimizasyon
• Robot Manipülatör
• Simülasyon
• Konum kontrolü

The Bees Algorithm Approach to Determining SMC Controller Parameters for the Position Control of a SCARA Robot Manipulator

Abstract

In this study, position control of a SCARA robot manipulator is investigated using the sliding mode control (SMC) method based on parameter optimization using The Bees Algorithm. The modeling the SCARA manipulator is conducted in MSC Adams and the control implementation is carried out in MATLAB software. The numerical model of the SCARA manipulator is acquired by setting up a virtual prototype on MSC Adams software. In addition, the inverse kinematic equations of the SCARA manipulator are formed using Matlab/Simulink software in order to check the accuracy of the created virtual prototype. In addition, the SMC controller parameters are optimized with The Bees Algorithm to get better results. Then, the control performance of the system is examined on the virtual prototype using MSC Adams-MATLAB co-simulation. Moreover, Genetic Algorithm, another meta-heuristic method, is used for parameter optimization and the performance of The Bees Algorithm is compared with the results obtained. As a result, it has been observed that The Bees Algorithm can be used in studies related to the control of robotic systems.

Keywords

• Optimization
• Position control
• Robot manipulator
• Sliding mode control
• Simulation
• The Bees Algorithm

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