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Title: Grey Wolf Optimizer Based Tuning of a Hybrid LQR-PID Controller for Foot Trajectory Control of a Quadruped Robot
Authors: Şen, Muhammed Arif
Kalyoncu, Mete
Keywords: Biyoloji
Kimya, Analitik
Kimya, Uygulamalı
Kimya, İnorganik ve Nükleer
Kimya, Tıbbi
Kimya, Organik
Fizik, Uygulamalı
Fizik, Atomik ve Moleküler Kimya
Fizik, Katı Hal
Fizik, Akışkanlar ve Plazma
Fizik, Matematik
Fizik, Nükleer
Fizik, Partiküller ve Alanlar
İstatistik ve Olasılık
Bilgisayar Bilimleri, Yapay Zeka
Bilgisayar Bilimleri, Sibernitik
Bilgisayar Bilimleri, Donanım ve Mimari
Bilgisayar Bilimleri, Bilgi Sistemleri
Bilgisayar Bilimleri, Yazılım Mühendisliği
Bilgisayar Bilimleri, Teori ve Metotlar
Mühendislik, Kimya
İnşaat Mühendisliği
Mühendislik, Elektrik ve Elektronik
Endüstri Mühendisliği
İmalat Mühendisliği
Mühendislik, Makine
Issue Date: 2019
Abstract: Quadruped robots have generally complex construction, so designing a stable controller for them is a major struggle task. This paper presents designing and optimization of an effective hybrid control by combining LQR and PID controllers. In this study, the tuning of a hybrid LQR-PID controller for foot trajectory control of a quadruped robot during step motion using Grey Wolf Optimizer (GWO) algorithm which is an alternative method are comparatively investigated with two traditional benchmarking algorithms (PSO and GA). The principal goal of this work is the tuning of the LQR controller parameters (Q and R weight matrices) and the PID controllers gains (kp, ki and kd) using the proposed algorithms. Initially, the designed solid model of the quadruped robot is imported into Simulink/SimMechanics which are simulation tools of MATLAB and then obtained the mathematical model of system which is at State-Space form with Linear Analysis Tools considering the step motion of robot leg in sagittal plane. Later, the hybrid LQR-PID control system is designed and its parameters are tuned to get optimal values which guarantee best trajectory tracing in Simulink with the three proposed algorithms. Subsequently, the system is simulated separately with optimal control parameters which provide from the algorithms. The simulation outcomes are indicating that GWO algorithm is more efficiently and quickly within similar torques to tuning the hybrid controller based on LQR&PID than the other conventional algorithms.
ISSN: 2147-1762
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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