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Design of robust fuzzy controller for ship course-tracking based on RBF network and backstepping approach 被引量:4

Design of robust fuzzy controller for ship course-tracking based on RBF network and backstepping approach
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摘要 This study presents an adaptive fuzzy neural network (FNN) control system for the ship steering autopilot. For the Norrbin ship steering mathematical model with the nonlinear and uncertain dynamic characteristics, an adaptive FNN control system is designed to achieve high-precision track control via the backstepping approach. In the adaptive FNN control system, a FNN backstepping controller is a principal controller which includes a FNN estimator used to estimate the uncertainties, and a robust controller is designed to compensate the shortcoming of the FNN backstepping controller. All adaptive learning algorithms in the adaptive FNN control system are derived from the sense of Lyapunov stability analysis, so that system-tracking stability can be guaranteed in the closed-loop system. The effectiveness of the proposed adaptive FNN control system is verified by simulation results.
出处 《Journal of Marine Science and Application》 2006年第3期5-10,共6页 船舶与海洋工程学报(英文版)
基金 Supported by Doctoral Bases Foundation of the Educational Committee of P. R. China under Grant No. 20030151005 and the Ministry of Communication of P. R. China under Grant No. 200332922505.
关键词 fuzzy neural network ship course-tracking adaptive control backstepping approach 模糊神经网络 船航向追踪 适应性控制 船舶自动驾驶仪
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