Rehabilitasyon Robotlarının Kontrolü için Bulanık Mantık ve PID Denetleyicinin Karşılaştırılması

Doğrusal olmayan bir sistemin yanıtı genellikle bir doğrusal denetleyici kullanılarak istenen bir modele göre şekillendirilemez. PID denetleyiciler gibi geleneksel model tabanlı doğrusal denetleyicilerle doğrusal olmayan durumların gerçekleştirilmesi zordur ve denetleyicinin düzgün çalışması için sıfırlama önleyici sarma, geciktirilmiş integral eylem vb. gibi birçok ek önlem dahil edilmelidir. Bu nedenle doğrusal olmayan sistemler için genellikle Bulanık Mantık Kontrol gibi kontrol yöntemleri kullanılır. Bulanık Mantık, gömülü kontrol için hem doğrusal hem de doğrusal olmayan sistemlerin geliştirilmesinde uygulanabilen alternatif bir tasarım metodolojisidir. Tasarımcılar, bulanık mantık kullanarak daha düşük geliştirme maliyetleri, üstün özellikler ve daha iyi son ürün performansı sağlayabilirler. Bu sebeple bu çalışmada rehabilitasyon robotlarının kontrolü için MATLAB/Simulink ortamında bir Bulanık Kontrol denetleyici tasarlanmıştır. Daha sonra kontrol etkisi analiz edilip PID denetleyicinin etkisiyle karşılaştırılmıştır. Karşılaştırma sonucunda bulanık mantık denetleyici, PID kontrolünden özellikle yanıt süresi, kararlı durumdaki hata ve aşım gibi çeşitli parametrelerde daha üstün performans sergilemiştir.

Comparison of Fuzzy Logic and PID Controller for Control of Rehabilitation Robots

The response of a nonlinear system cannot usually be shaped into a desired model using a linear controller. Non-linear situations are difficult to realize with traditional model-based linear controllers such as PID controllers, and anti-reset winding, delayed integral action, etc., are required for the controller to work properly. Many additional measures should be included, such as for this reason, control methods such as Fuzzy Logic Control are often used for nonlinear systems. Fuzzy Logic is an alternative design methodology that can be applied to the development of both linear and nonlinear systems for embedded control. By using fuzzy logic, designers can achieve lower development costs, superior features, and better end-product performance. For this reason, in this study, a Fuzzy Control controller was designed in MATLAB/Simulink environment for the control of rehabilitation robots. Then the control effect was analyzed and compared with the effect of the PID controller. As a result of the comparison, the fuzzy logic controller outperformed the PID control in various parameters such as response time, steady state error and overshoot.

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