Paper
2 November 2022 Encoder sinusoidal error compensation based on optimized PSO algorithm
Author Affiliations +
Proceedings Volume 12351, International Conference on Advanced Sensing and Smart Manufacturing (ASSM 2022); 123511J (2022) https://doi.org/10.1117/12.2654573
Event: International Conference on Advanced Sensing and Smart Manufacturing (ASSM 2022), 2022, Nanjing, China
Abstract
Encoders have the advantages of high precision and reliability, and are widely used in industries such as industry and aviation and military industries. As Industry 4.0 puts forward higher requirements for encoder output accuracy, this paper proposes a subdivision error compensation model of particle swarm network based on adaptive subdivision. Through the parallel iterative particle swarm optimization model, the error compensation of the encoder output grating signal is realized. The problems in the past particle swarm optimization models, such as slow convergence speed and easy to fall into local optimum, are optimized. The optimization algorithm can effectively improve the convergence speed and system accuracy of traditional particle swarm optimization.
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Han Hou, Guo-hua Cao, Hongchang Ding, and Kun Li "Encoder sinusoidal error compensation based on optimized PSO algorithm", Proc. SPIE 12351, International Conference on Advanced Sensing and Smart Manufacturing (ASSM 2022), 123511J (2 November 2022); https://doi.org/10.1117/12.2654573
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KEYWORDS
Particles

Error analysis

Particle swarm optimization

Optimization (mathematics)

Sensors

Signal processing

Prisms

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