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Optimisation-oriented active disturbance rejection control for dynamic positioning ships using improved Salp Swarm Algorithm
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AI
DOI：10.1080/20464177.2026.2641360.png)
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Abstract
En 中文
The advancement of modern maritime operations increasingly depends on reliable and intelligent control technologies. Dynamic Positioning (DP) serves as a crucial guarantee for the stable operation of marine vessels. Nevertheless, owing to the inaccuracies and coupling effects in ship dynamic models, designing a controller that can adapt to the complex marine environment remains a formidable challenge. Given the chattering and phase lag issues in the traditional Active Disturbance Rejection Controller (ADRC), this paper proposes a nonlinear filtering module and a phase compensator to improve ADRC performance. Additionally, to minimise the impact of noise on the Tracking Differentiator (TD), the traditional fast optimal control module is replaced with a hyperbolic tangent function. Moreover, to optimise the multiple internal parameters of the Improved ADRC (IADRC), this paper adopts the Salp Swarm Algorithm (SSA). Due to the tendency to fall into local optima, the low convergence accuracy and the slow convergence speed of SSA, this paper proposes Tent mapping, a disturbance factor and an adaptive rate to ameliorate the parameters optimisation. The relative simulation results show that the DP system with Improved SSA (ISSA)-based IADRC has the advantages of small tracking error and strong disturbance rejection capability.
Keywords:
Dynamic Positioning
Active Disturbance Rejection Control
Salp Swarm Algorithm
Ship Control
Parameter Optimisation
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J
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Papers:
37
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