Genetik Algoritma ile Optimize Edilmiş Alçak Geçiren Filtre içeren PID Denetleyici Kullanılarak Süspansiyon Sistemi Kontrol Performansının Artırılması

Abstract

Bu çalışmada, süspansiyon sistemlerinin kontrolü için yaygın olarak kullanılan PID kontrolcünün performansını arttırmak için bir filtre eklenmiştir. Bu filtre tasarlanırken, klasik PID kontrolcü filtrelerinden farklı olarak, kayan kipli kontrolcülerde çatırtıyı ve sistem parametrelerindeki belirsizlikleri önlemek için kullanılan düşük geçirgen filtreden esinlenilmiştir. Ayrıca filtrelenen kuvvet değeri, katsayıya dayalı bir denklem kullanılarak PID kontrolcüden elde edilen kuvvet değeri ile birleştirilmiş ve filtre katsayıları genetik algoritma aracılığıyla optimize edilmiştir. Yapılan optimizasyon sonucunda tasarlanan kontrolcü, karşılaşılabilecek çeşitli yol girişleri için simule edilerek sonuçlar elde edilmiştir. Kontrolcüsüz ve filtresiz PID kontrolcü ile elde edilen sonuçlar kıyaslanarak, tasarlanan kontrolcünün başarımı IAE ve ISE kriterlerine göre açıkça gösterilmiştir. Kontrolcünün gürbüzlüğü değişen kütle koşulları altında değerlendirilmiş ve performansı tablo halinde verilmiştir.

Keywords

• Filtreli PID
• Genetik Algoritma
• Aktif Süspansiyon Sistemleri
• Gürbüz Kontrol

Enhancing Suspension System Control Performance Using PID Controller Incorporated Low-Pass Filter Optimizated with Genetic Algorithm

Abstract

In this study, a filter has been incorporated to enhance the performance of the PID controller, which is commonly used for controlling suspension systems. While designing this filter, the insipration has been the low-pass filter used in sliding mode controllers to prevent chattering and uncertainties in system parameters, unlike conventional PID controller filters. Additionally, the filtered force value was combined with the force value obtained from the PID controller using an equation based on a coefficient, and filter coefficients were optimized through genetic algorithms. As a result of the optimization, the designed controller was simulated for various road inputs that could be encountered, and results were obtained. By comparing the results obtained with a PID controller without a filter and without a controller, the performance of the designed controller is clearly shown according to IAE and ISE criteria. Robustness of the controller was evaluated under varying mass conditions and its performance was given as a table.

Keywords

• Filter PID
• Genetic Algorithm
• Active Suspension Systems
• Robust Control

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