计算机应用 ›› 2010, Vol. 30 ›› Issue (8): 2260-2264.
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汪明慧1,余永权2,曾碧2
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摘要： 针对常规模糊自动舵由于受船舶控制过程的非线性、时变性以及风浪干扰等因素影响,模糊控制规则和隶属函数需要校正，利用神经网络的自学习能力，用神经网络去实现模糊控制，设计自动舵神经模糊控制器，采用BP算法和最小二乘算法的混合学习算法实现对模糊规则和隶属函数的参数训练，提高控制器的自适应能力。仿真实验表明所设计的控制器有效可行，适应船舶在风浪干扰环境下的控制性能要求。
关键词: 神经模糊控制、自动舵、混合学习算法
Abstract: Neuro-fuzzy control technology was applied to marine autopilot. The nero-fuzzy controller for autopilot was designed in this paper. Learning ability of neural network was utilized to optimize the fuzzy controller. Hybrid learning rule, a combination of Back Propagation algorithm (BP) and Least Square Estimator (LSE), was utilized to realize parameter adjustment of fuzzy control rule and membership function in order to improve the adaptive capacity of the controller. The simulation result shows that the controller designed is effective and feasible to satisfy the control performance requirements when marine is under wave interference.
Key words: Neuro-Fuzzy Control ,Autopilot, Hybrid Learning Rule
汪明慧 余永权 曾碧. 神经模糊控制在船舶自动舵中的应用[J]. 计算机应用, 2010, 30(8): 2260-2264.
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http://www.joca.cn/CN/Y2010/V30/I8/2260
