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Broad learning system-based adaptive optimal control design for dynamic positioning of marine vessels

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Abstract

This paper investigates a discrete-time (DT) adaptive optimal control policy based on broad learning system (BLS) and adaptive dynamic programming (ADP) for dynamic positioning (DP) of marine vessels, focusing on the unknown system dynamics, fuel saving and pollution reduction. Firstly, a BLS-based model structure in ADP is utilized to identify the unknown system dynamics. The weights of this flat architecture can be calculated without the process of iteration. Then, critic and action structures in ADP are established by two BLSs to solve the optimal problems of fuel saving and pollution reduction. These two structures are utilized to approximate the optimal performance index function and controller, respectively. The weights of these two structures are updated with the current and historical data. The proposed adaptive optimal controller is proved to be able to hold the vessel at a fixed position and heading in a more energy-saving and time-saving way than traditional neural network (NN)-based ADP method. It is proved that all the signals in the closed-loop DP system guarantee the uniform ultimate boundedness (UUB) simultaneously. Finally, simulations and comparisons are provided to illustrate the validity of the proposed adaptive optimal control scheme.

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Data Availability Statement

The experimental data of the DP model and BLS can be found in [35] and [43], respectively. The code of this paper is not available.

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Authors and Affiliations

  1. Navigation College, Dalian Maritime University, Dalian, 116026, Liaoning, China

    Xiaoyang Gao, Tieshan Li & Liang’en Yuan

  2. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China

    Weiwei Bai, Tieshan Li & Yue Long

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  1. Xiaoyang Gao
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  2. Weiwei Bai
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  3. Tieshan Li
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Correspondence to Weiwei Bai or Tieshan Li.

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This work is supported in part by the National Natural Science Foundation of China (under Grant Nos. 51939001, 61976033, 61903092); the Science and Technology Innovation Funds of Dalian (under Grant No. 2018J11CY022); the Liaoning Revitalization Talents Program (under Grant Nos. XLYC1908018); the Natural Foundation Guidance Plan Project of Liaoning (under Grant Nos. 2019-ZD-0151, 2020-HYLH-26); the Fundamental Research Funds for the Central Universities (under Grant No. 3132019345); the Doctoral Innovation Project of Dalian Maritime University (under Grant No. BSCXXM002).

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Gao, X., Bai, W., Li, T. et al. Broad learning system-based adaptive optimal control design for dynamic positioning of marine vessels. Nonlinear Dyn 105, 1593–1609 (2021). https://doi.org/10.1007/s11071-021-06634-6

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