A Fuzzy Compensation Control System for Underwater Vehicle Based on Kalman Filter Predictor

Abstract:

Article Preview

This paper presents a novel control system for underwater vehicle. The underwater vehicle is affected by the inevitable surge and measurement error when working. In order to achieve reliable and quick control characteristic, this paper realize the control system by fuzzy compensation based on Kalman predictor with iterative control response. With this predictor and the control error, the fuzzy controller calculates the control compensation, and then the underwater vehicle completes a fast response control. By the control simulation, the results show that the method is effective and feasible.

Info:

Periodical:

Advanced Materials Research (Volumes 383-390)

Edited by:

Wu Fan

Pages:

580-583

Citation:

Z. J. Tang et al., "A Fuzzy Compensation Control System for Underwater Vehicle Based on Kalman Filter Predictor", Advanced Materials Research, Vols. 383-390, pp. 580-583, 2012

Online since:

November 2011

Export:

Price:

$38.00

[1] Serrani, A.; Conte, G.: Robust nonlinear motion control for AUVs. in: Robotics & Automation Magazine, IEEE, Vol. 6, 1999: 33 - 38, 62.

DOI: https://doi.org/10.1109/100.774926

[2] P. -M. Lee, S. -W. Hong, Y. -K. Lim, C. -M. Lee, B. -H. Jeon and J. -W. Park: Discrete-time quasi-sliding mode control of an autonomous underwater vehicle. In: IEEE Journal of Oceanic Engineering, p.388–395, (1999).

DOI: https://doi.org/10.1109/48.775300

[3] Xiaocheng Shi, Huashen Xiong, Chunguo Wang and Zonghu Chang:A New Model of Fuzzy CMAC Network with Application to the Motion Control of AUV. In: Proceedings of the IEEE International Conference on Mechatronics & Automation Niagara Falls, pp.2173-2178, Canada(2005).

DOI: https://doi.org/10.1109/icma.2005.1626901

[4] F. Song and S.M. Smith: Design of sliding mode fuzzy controllers for an autonomous underwater vehicle without system model. In: MTS/IEEE Oceans, pp.835-840, (2000).

DOI: https://doi.org/10.1109/oceans.2000.881362

[5] Bin Xu, Norimitsu Sakagami, Shunmugham R. Pandian and Fred Petry: A Fuzzy Controller for Underwater Vehicle-Manipulator Systems. In: MTS/IEEE Oceans, p.1110 – 1115, (2005).

DOI: https://doi.org/10.1109/oceans.2005.1639905

[6] Chuan-Kai Lin: Adaptive Critic Control of Autonomous Underwater Vehicles Using Neural Networks. In: Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications, p.122 – 127, (2006).

DOI: https://doi.org/10.1109/isda.2006.253817

[7] Silvia M Zanoli, Giuseppe Conte : Remotely operated vehicle depth control, Control Engineering Practice,Vol. 11, 2003: 453-459.

DOI: https://doi.org/10.1016/s0967-0661(02)00013-8

[8] T. I. Fossen and S. I. Sagatun: Adaptive control of nonlinear systems: A case study of underwater robotic systems. In: Journal of Robotic Systems, p.392–342, (1991).

DOI: https://doi.org/10.1002/rob.4620080307

Fetching data from Crossref.
This may take some time to load.