Grey Wolf Optimizer Based Tuning of a Hybrid LQR-PID Controller for Foot Trajectory Control of a Quadruped Robot

Year 2019, Volume: 32 Issue: 2, 674 - 684, 01.06.2019

Muhammed Arif Şen , Mete Kalyoncu

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.

Keywords

Quadruped Robot, Grey Wolf Optimizer, Leg Trajectory Control, Tuning Hybrid LQR-PID, Grey Wolf Optimizer, PSO

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