Abstract
This paper presents a predictive control approach based on ant colony optimization algorithm for critical maneuvering of unmanned surface vehicle in high sea environment. The algorithm uses the generalized predictive control to get the predictive course value. In the process of the algorithm, the ant colony algorithm is used to obtain the optimal control sequence of the rudder angle. The obtained simulation results show that the algorithm solves the problem of overshoot of course controller, and realizes the precise control of USV course in the case of large disturbance of wind and wave, then solves the saturation nonlinear problem of unmanned surface vessel in extreme sea condition.
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Zhao, D., Yang, T., Ou, W., Zhou, H. (2017). Predictive Controller Design Using Ant Colony Optimization Algorithm for Unmanned Surface Vessel. In: He, C., Mo, H., Pan, L., Zhao, Y. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2017. Communications in Computer and Information Science, vol 791. Springer, Singapore. https://doi.org/10.1007/978-981-10-7179-9_44
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DOI: https://doi.org/10.1007/978-981-10-7179-9_44
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