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Comparative analysis of Mamdani and Sugeno type fuzzy autopilots for ships

机译:Mamdani型和Sugeno型模糊自动驾驶仪的对比分析

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In this paper a comparative analysis of Mamdani and Sugeno type fuzzy autopilots for ships is given. Both autopilots have two inputs: the heading signal and the yaw rate signal, and only one output: command rudder angle. Input variable fuzzification, fuzzy associative memory (FAM) rules, and output set defuzzification are described. The control system for the course-keeping composed of the nonlinear ship, the steering gear servo system, fuzzy autopilot and wave disturbance is described. Both autopilots are compared in three different sailing conditions: without wave disturbance, with wave disturbance and with wave disturbance and wave filtering. The notch filter was used for filtering of second-order wave disturbances. The influence of wave disturbance on course-keeping performance was analyzed. Even though the obtained performance in simulations are very similar, authors prefer Sugeno type fuzzy autopilot, due to less strain of the steering gear servo system and faster and more accurate heading obtained.
机译:本文对船舶的Mamdani型和Sugeno型模糊自动驾驶仪进行了比较分析。两个自动驾驶仪都有两个输入:航向信号和偏航角速度信号,只有一个输出:指令舵角。描述了输入变量模糊化,模糊联想记忆(FAM)规则和输出集模糊化。描述了由非线性船舶,舵机伺服系统,模糊自动驾驶仪和波浪干扰组成的航向控制系统。在三种不同的航行条件下比较了两种自动驾驶仪:无波浪干扰,有波浪干扰以及有波浪干扰和波浪滤波。陷波滤波器用于滤除二阶波干扰。分析了波浪干扰对课程保持性能的影响。尽管在模拟中获得的性能非常相似,但由于转向齿轮伺服系统的应变较小且获得的航向更快,更准确,因此作者更喜欢Sugeno型模糊自动驾驶仪。

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