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Tuning of LQR-PID controller to control parallel manipulator

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Abstract

The paper presents mathematical modeling and optimal path control of a 3-DOF Maryland manipulator. Three dissimilar and consecutive paths are taken under observation, and control action is performed by linear quadratic regulator (LQR)-based proportional–integral–derivative (PID) controller. To achieve optimal path tracking control, tuning of PID gain parameters is necessary and it is done by optimal selection of weighting matrices of LQR. The evolutionary optimization algorithms like GA and PSO are used in the past for the optimal selection of LQR parameters for tuning of PID gain parameter, but both the methods fail to achieve accurate trajectory tracking control because the simulation results show higher values of fitness function (J), sum square error, integral square error, and integral absolute error between the desired and the actual trajectory for all joint angles, as discussed in the result analysis section. The gray wolf optimizer (GWO) algorithm is then proposed; this method provides optimal values of gain parameters. The simulation results show that the values of all types of error and fitness function for all joint angles are quite lesser than GA and PSO. Hence, the proposed GWO proves better among all and it provides high accuracy in trajectory tracking control with better performance indices. To demonstrate the proposed algorithm, the mathematical simulations are performed as well as the conduction of experimental work.

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Authors and Affiliations

  1. Electrical Department, Dronacharya Group of Institutions, Greater Noida, Uttar Pradesh, India

    Chandan Choubey

  2. Electrical Department, NIT Kurukshetra, Kurukshetra, Haryana, India

    Jyoti Ohri

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  1. Chandan Choubey
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  2. Jyoti Ohri
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Correspondence to Chandan Choubey.

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Choubey, C., Ohri, J. Tuning of LQR-PID controller to control parallel manipulator. Neural Comput & Applic 34, 3283–3297 (2022). https://doi.org/10.1007/s00521-021-06608-0

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