Uncertainty optimisation design of USV based on the Six Sigma method

Abstract

In order to improve the sailing performance of unmanned surface vehicles (USVs), maximise the value of their sailing performance function, and minimise disturbances caused by uncertainty factors, this study introduces a 6σ theory of quantitative descriptions of uncertainty levels into the USV sailing performance optimisation model. It uses the Multi-Island Genetic Algorithm to optimise the certainty of the design variables and plot the optimal curve and the Monte Carlo simulation to analyse the sensitivity of the total objective function. The Mean on target and the Minimise variation function are used for the 6σ optimisation. The uncertainty factors are the floating range of the design variables. Results indicate that the design variables affect the value of the total objective function. A comparative analysis of the certainty optimisation results and the results obtained by the 6σ uncertainty optimisation shows that although the value of the latter’s total objective function decreases, its reliability is greatly improved. The 6σ optimisation method, therefore, can be applied to improve the sailing performance design of USVs and obtain reasonable and highly reliable results, which can ensure that the constraint condition has a high degree of immunity to the uncertainty of actual situations.

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ORCID for Yeping Xiong: orcid.org/0000-0002-0135-8464

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