Robust fuzzy 3D path following for autonomous underwater vehicle subject to uncertainties

Xia, Xiang; Yu, Caoyang; Zhang, Qin

doi:10.1016/j.cor.2016.09.017

Cited by 244 publications

(81 citation statements)

References 44 publications

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“…This is even more prominent for the underwater vehicles [25] . The function of the adaptive controller is confronted with greatness challenge since marine control applications are characterized by widely changing sea conditions and unmodeled dynamics [26] .…”

Section: Introductionmentioning

confidence: 99%

Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed

Wang

Liu

2018

Neurocomputing

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Section: Introductionmentioning

confidence: 99%

Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed

Wang

Liu

2018

Neurocomputing

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“…For a class of discrete systems with multiple delays and disturbances, Teng et al [12] proposed a Takagi-Sugeno fuzzy approach to achieve the robustness of model predictive control. Compared with most of the existing methods for 3D path following, the robust fuzzy control scheme proposed by Xiang et al [14] can be more effective in reducing the implementation costs of complicated dynamics controller and environmental disturbances. By taking account of the 2 Complexity location effect, dispersion effect, and model uncertainty of the multiple responses simultaneously, He et al [19] developed a robust fuzzy programming approach to solve the multiple responses optimization problems, which can ensure the robustness of the system.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the above literatures did not take into account the robustness of the supply chain system after compressing the lead time. In order to improve the robustness of the system, some scholars have applied the robust control method and the robust optimization method [12][13][14][15][16][17][18][19]. For a class of discrete systems with multiple delays and disturbances, Teng et al [12] proposed a Takagi-Sugeno fuzzy approach to achieve the robustness of model predictive control.…”

Section: Introductionmentioning

confidence: 99%

Decision of Lead-Time Compression and Stable Operation of Supply Chain

Zhang¹,

Li²,

Zhang³

et al. 2017

Complexity

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A cost optimization strategy and a robust control strategy were studied to realize the low-cost robust operation of the supply chain with lead times. Firstly, for the multiple production lead times which existed in the supply chain, a corresponding inventory state model and a supply chain cost model were constructed based on the Takagi-Sugeno fuzzy control system. Then, by considering the actual inventory level, the lead-time compression cost, and the stock-out cost, a cost optimization strategy was proposed. Furthermore, a fuzzy robust control strategy was proposed to realize the flexible switching among the models. Finally, the simulation results show that the total cost of the supply chain could be reduced effectively by the cost optimization strategy, and the stable operation of the supply chain could be realized by the proposed fuzzy robust control strategy.

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“…However, as the electromagnetic waves decay rapidly in water, the popular Global Positioning System (GPS) cannot be used locate the AUV. [4][5][6] The research of the positioning technology is of great significance. Acoustic wave, as the only information carrier in water, provides a viable alternative to locate AUV.…”

Section: Introductionmentioning

confidence: 99%

Optimal distance for moving long baseline positioning system with distance-dependent measurement noise

Chen

Sun

2018

Advances in Mechanical Engineering

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This article investigates the effect of distance-dependent noise on optimal transponder distance in a moving long baseline positioning system. First, according to the positioning model of the moving long baseline positioning system, the relationship between measurement noises and positioning error is established. Second, a cost function is proposed to evaluate the positioning performance. Then, based on the optimal formation, the optimal distance is deduced. Finally, the relationship between the optimal distance and the parameter for the distance-dependent error is proposed. By using this relationship, the effect of distance-dependent measurement noise on optimal distance is analyzed. Simulation examples illustrate the results.

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Robust fuzzy 3D path following for autonomous underwater vehicle subject to uncertainties

Cited by 244 publications

References 44 publications

Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed

Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed

Decision of Lead-Time Compression and Stable Operation of Supply Chain

Optimal distance for moving long baseline positioning system with distance-dependent measurement noise

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