Abstract
An intelligent PID control algorithm is designed for ship’s course tracking control. As known to all, the deficiencies of traditional PID control is that its parameters cannot be adjusted in real time, and thus control effect is not perfect. To this end, Genetic Algorithm is used to optimize PID parameters in this paper in order to achieve feedback control and to ensure system stability. CMAC neural network is used to achieve feed-forward nonlinear control, and to restrain internal and external disturbance for ensuring satisfied control accuracy and response speed of system. The result of simulations shows that the controller devised in the paper has superior performance and strong robustness.
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Acknowledgments
This work is supported by Foundation of Jiangsu Maritime Institute under Grant No. XR1501 and No. 2015KJZD-01.
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Sun, J., Wang, R., Yu, K., Miao, K., Deng, H. (2018). Application of Genetic Algorithm and Neural Network in Ship’s Heading PID Tracking Control. In: Qiao, F., Patnaik, S., Wang, J. (eds) Recent Developments in Mechatronics and Intelligent Robotics. ICMIR 2017. Advances in Intelligent Systems and Computing, vol 691. Springer, Cham. https://doi.org/10.1007/978-3-319-70990-1_64
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DOI: https://doi.org/10.1007/978-3-319-70990-1_64
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