GPU-Implementation of a Sequential Monte Carlo Technique for the Localization of an Ackerman Robot

Garcia-Bedoya, Olmer; Acosta, David; Díaz, Carlos

doi:10.1007/978-3-030-01535-0_23

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“…In other swarm intelligence algorithms, the estimated mathematical models of systems or processes can be used to modify the parameters of PID controllers. These adaptive control strategies can be implemented in commercial programmable logic controllers (PLC) [9,10].…”

Section: Introductionmentioning

confidence: 99%

Control scheme selection and optimal tuning in industrial process control using factorial experiment design

Acosta¹,

Polania

Verdeza-Villalobos³

et al. 2020

redin

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In this study, a novel experimental approach for the optimal selection of an actuator-based control strategy is presented. The proposed approach is a two-stage method: first, a two-level factorial experiment design with n factors (2n) was applied to compare different control schemes. Schemes comparison was carried out in terms of energy consumption and closed-loop performance. For the best relative scheme, a Central Composite Face-centered (CCF) design was completed obtaining the controller parameters that optimize the performance in terms of the Integral Absolute Error (IAE) while operating in a region of low energy consumption. The proposed approach was experimentally tested using real data obtained from a laboratory prototype plant. Some experimental tests illustrating the suitability of our method are shown at the end of this article.

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Section: Introductionmentioning

confidence: 99%