GWO-BASED TUNING OF LQR–PID CONTROLLER FOR 3-DOF PARALLEL MANIPULATOR

Chandan Choubey∗ and Jyoti Ohri∗∗

Keywords

Parallel manipulator, trajectory control, tuning LQR–PID, GA algorithm, PSO algorithm, GWO algorithm

Abstract

This article presents mathematical modelling and optimal trajec- tory tracking control of a 3-degree-of-freedom parallel manipulator, well known as Maryland manipulator. Three unlike sequential tra- jectories are considered, and the trajectory tracking control of a manipulator is performed by linear quadratic regulator (LQR)- proportional-integral-derivative (PID) controller. The tuning of LQR–PID is done by using grey wolf optimizer (GWO) which is a meta-heuristic method, compared with two other traditional bench- marking algorithms, i.e., particle swarm optimizer (PSO) and ge- netic algorithm (GA). According to the obtained simulation results, the proposed GWO methodology is more efficient and accurate in trajectory tracking control and generates optimal torques to the input links of the manipulator as compared with other evolutionary optimization algorithms like PSO and GA.

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