GWO-Based Tuning of LQR-PID Controller for a 3-DOF Parallel Manipulator

Abstract

This paper presents the mathematical modeling and optimal trajectory tracking control of a 3-degree-of-freedom parallel manipulator, commonly known as Maryland manipulator. Three unlike sequential trajectories are considered, and the trajectory-tracking control of a manipulator is performed by the LQR-PID controller. The tuning of LQR-PID is done by using the Grey Wolf Optimizer (GWO), a meta-heuristic method. The two other traditional benchmarking algorithms are Particle Swarm Optimizer (PSO) and Genetic Algorithm (GA). The main goal of this work is to calculate the optimum values of LQR gain parameters i.e. Q and R matrices and PID controller’s gains i.e. K_p, K_i and K_d using three different optimization algorithms, and their performance comparisons are highlighted in simulation results and discussion section. According to the obtained simulation results, the proposed GWO methodology is more efficient and more accurate in trajectory tracking control and generates optimal torques to the input links of the manipulator when compared with other evolutionary optimization algorithms such as PSO and GA.

KEYWORDS:

• GA algorithm
• GWO algorithm
• parallel manipulator
• PSO algorithm
• Trajectory control
• Tuning LQR-PID
• Torques

Additional information

Notes on contributors

Chandan Choubey

Chandan Choubey received BTech degree from Uttar Pradesh Technical University, Lucknow in 2008, MTech degree from National Institute of Technology Kurukshetra in 2010. Presently, he is working as assistant professor in Dronacharya Group of Institution, Greater Noida and pursuing his doctorate degree in the field of robotics and its control from NIT Kurukshetra. His areas of interest include Robotic system and its control, optimization, soft computing and its application for the dynamics and control of parallel manipulators.

Jyoti Ohri

Jyoti Ohri received her PhD from National Institute of Technology, Kurukshetra in 2010. Presently, she is working as professor in the Department of Electrical Engineering at National Institute of Technology, Kurukshetra. Her research interests include robust and adaptive control, optimization, instrumentation and robotics. Email: [email protected]