Optimal Tuning of PID Controller Using Grey Wolf Optimizer Algorithm for Quadruped Robot

Abstract

The research and development of quadruped robots is grown steadily in during the last two decades. Quadruped robots present major advantages when compared with tracked and wheeled robots, because they allow locomotion in terrains inaccessible. However, the design controller is a major problem in quadruped robots because of they have complex structure. This paper presents the optimization of two PID controllers for a quadruped robot to ensure single footstep control in a desired trajectory using a bio-inspired meta-heuristic soft computing method which is name the Grey Wolf Optimizer (GWO) algorithm. The main objective of this paper is the optimization of KP, KI and KD gains with GWO algorithm in order to obtain more effective PID controllers for the quadruped robot leg. The importance to this work is that GWO is used first time as a diversity method for a quadruped robot to tune PID controller. Moreover, to investigate the performance of GWO, it is compared with widespread search algorithms. Firstly, the computer aided design (CAD) of the system are built using SolidWorks and exported to MATLAB/SimMechanics. After that, PID controllers are designed in MATLAB/Simulink and tuned gains using the newly introduced GWO technique. Also, to show the efficacy of GWO algorithm technique, the proposed technique has been compared by Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. The system is simulated in MATLAB and the simulation results are presented in graphical forms to investigate the controller's performance.

Online 3D path planning for Tri-copter drone using GWO-IBA algorithm

“…Delta wolves depend on the beta and alpha, but they command on the omega, and the rest of the wolf group count as omega. In this optimization method (GWO), the optimal solutions are leading by alpha, beta, and delta [16], [17]. They lead residue wolves (omega) to the optimal point in the searching area, as shown in Figure 2.…”

A Literature Review on Walking Strategies of Legged Robots

“…Yukarda değinildiği üzere birçok başarılı robotun başlangıç noktasının ilk önce tek bir bacak üzerine yapılan araştırma çalışmaları olmasından dolayı, Kalyoncu ve ekibi çalışmalarına, dört ayaklı bir robot için bir bacak tasarımı da dahil olmak üzere, ilk önce yürüyüşün kendisi ile değil de yürüyüş performansını doğrudan etkileyen adım atma performansı ve adım kontrolü üzerine yaptıkları araştırmalar ile başlamışlardır. Devamında farklı çalışma şartları için adım refleksinin iyileştirilmesi ile yürüyüş performansının artırılması ve dört ayaklı bir robotun ters kinematik analizi gibi konular üzerine yaptıkları araştırmalar ile çalışmalarına devam etmişlerdir [185][186][187][188][189][190][191].…”

Steady state analysis of modern industrial variable speed drive systems using controllers adjusted via grey wolf algorithm & particle swarm optimization

“…GWO algorithm is an improved version of PSO algorithm and it was proposed in this paper to find the optimal values for the parameters of the controllers used in the study. In 2014, MIRJALILI et al [16,17], developed the grey wolf optimization algorithm which emulates the hierarchy of leadership in wolves known as group hunting. The grey wolf is a part of the CANIDAE family.…”

“…In 2014, MIRJALILI et al. [ 16 , 17 ], developed the grey wolf optimization algorithm which emulates the hierarchy of leadership in wolves known as group hunting. The grey wolf is a part of the CANIDAE family.…”

“…Optimization algorithms such as particle swarm optimization algorithm PSO, genetic algorithm GA, and others have demonstrated high efficiency and good results by improving steady state characteristics [9,10,11,12,13,14,15,16,17,18,19,20]. Some of the VSDSs used in modern industrial applications have demonstrated some important features, such as simplicity, easiness, and high reliability of the application.…”