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This paper researches how to apply the advanced control technology of model predictive control(MPC) to the design of the dynamic positioning system(DPS) of a semi-submersible platform.First,a linear low-frequency motion model with three degrees of freedom was established in the context of a semi-submersible platform.Second,a model predictive controller was designed based on a model which took the constraints of the system into account.Third,simulation was carried out to demonstrate the feasibility of the controller.The results show that the model predictive controller has good performance and good at dealing with the constraints of the system. 相似文献
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基于目标规划的水下机器人模糊神经网络控制 总被引:1,自引:0,他引:1
针对水下机器人运动的精确控制问题,依据模糊逻辑和神经网络理论,提出了一种基于目标规划的模糊神经网络控制方法。根据水下机器人的运动特性构造了模糊神经网络的结构,并推导了网络权值学习的反传算法,最后以水下综合探测机器人为研究对象进行了试验研究。试验研究的结果表明,该方法结合了传统模糊控制和神经网络控制的优点,大大地提高了系统响应速度和控制精度,并且对模型的不确定性有较强的鲁棒性,能够实现水下机器人运动的精确控制,具有较高的理论和实用价值。 相似文献