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

The research and development of quadruped robotsis grown steadily in during the last two decades. Quadruped robotspresent major advantages when compared with tracked andwheeled robots, because they allow locomotion in terrainsinaccessible. However, the design controller is a major problem inquadruped robots because of they have complex structure. Thispaper presents the optimization of two PID controllers for aquadruped robot to ensure single footstep control in a desiredtrajectory using a bio-inspired meta-heuristic soft computingmethod which is name the Grey Wolf Optimizer (GWO)algorithm. The main objective of this paper is the optimization ofKP, KI and KD gains with GWO algorithm in order to obtain moreeffective PID controllers for the quadruped robot leg. Theimportance to this work is that GWO is used first time as adiversity method for a quadruped robot to tune PID controller.Moreover, to investigate the performance of GWO, it is comparedwith widespread search algorithms. Firstly, the computer aideddesign (CAD) of the system are built using SolidWorks andexported to MATLAB/SimMechanics. After that, PID controllersare designed in MATLAB/Simulink and tuned gains using thenewly introduced GWO technique. Also, to show the efficacy ofGWO algorithm technique, the proposed technique has beencompared by Genetic Algorithm (GA) and Particle SwarmOptimization (PSO) algorithm. The system is simulated inMATLAB and the simulation results are presented in graphicalforms to investigate the controller’s performance.

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