Digital Twin-Based Fractional Order Controller Optimization for Industrial Robot

2021 ◽  
Author(s):  
Xuan Liu ◽  
Pengchong Chen ◽  
Ying Luo

Abstract In this paper, a practical and systematic tuning procedure for fractional order controller using particle swarm algorithm (PSO) based on digital twin (DT) system of industrial robot has been developed. The procedure includes a virtual realization of control system based on digital twin concept. Then a particle swarm algorithm is introduced to optimize the five parameters of the cascade fractional order PI-PIλ controller. The optimization procedure using particle swarm algorithm based on digital twin concept is also presented. Finally, the virtual industrial robot model in digital twin is simulated to verify the applicability of the optimization method. The effectiveness of using the cascaded fractional order PI-PIλ controller compared to the cascaded integer order PI-PI controller is illustrated by the simulation results, where the cascaded fractional order PI-PIλ controller responses faster with smaller tracking error over the integer order one.

Author(s):  
Honglei Xu ◽  
Linhuan Wang

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.


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