在复杂多变的海上运行环境下，针对减少船舶燃气轮机启动过程中的响应滞后时间、有效抑制外界干扰以及确保转速能够迅速达到并稳定至设定值的问题，提出了船舶燃气轮机启动转速自适应模糊滑模控制方法。通过Rowen模型，建立船舶燃气轮机数学模型；以该模型为基础，利用自适应模糊滑模控制算法，设计船舶燃气轮机启动转速控制器；采用变论域自适应模糊PID算法，根据实时转速偏差及其变化率，输出滑模控制器的自适应参数，用于调整滑模控制器的行为，以更好地抑制外界干扰；滑模控制器依据自适应参数，设计控制律，实现船舶燃气轮机启动转速的快速响应，减少响应滞后时间，使转速能够迅速达到并稳定至设定值。实验证明，该方法可有效快速控制船舶燃气轮机启动转速，负载扰动情况下，该方法启动转速控制的超调量较小。
In the complex and ever-changing offshore operating environment, in order to reduce the response lag time during the start-up process of ship gas turbines, effectively suppress external interference, and ensure that the speed can quickly reach and stabilize to the set value, a self-adaptive fuzzy sliding mode control method for the starting speed of ship gas turbines is proposed. The mathematical model of Marine gas turbine is established by Rowen model. Based on the model, the adaptive fuzzy sliding mode control algorithm is used to design the starting speed controller of Marine gas turbine. The adaptive fuzzy PID algorithm in variable theory domain is used to output the adaptive parameters of the sliding mode controller according to the real-time speed deviation and its rate of change, which can be used to adjust the behavior of the sliding mode controller to restrain the external interference better. According to the adaptive parameters, the sliding mode controller designs the control law to realize the fast response of the starting speed of Marine gas turbine and reduce the response lag time, so that the speed can quickly reach and stabilize to the set value. Experimental results show that this method can effectively and quickly control the starting speed of Marine gas turbine, and the overshoot of the starting speed control is small under load disturbance.
2024,46(24): 67-71 收稿日期：2024-10-11
DOI：10.3404/j.issn.1672-7649.2024.24.012
分类号：TK472
基金项目：湖北省教育厅科技处课题资助项目（B2017512）
作者简介：田彪(1982-),男,硕士,中级(轮机长)/讲师/实验师,研究方向为船舶轮机工程
参考文献：
[1] 杨福正, 刘宇骁, 柴运强, 等. 船舶燃气轮机冷却风机压头对排气引射系统流场特性的影响[J]. 热能动力工程, 2024, 39(6): 59-66+88.
[2] 岳有军, 程敏, 赵辉, 等. 自适应惯量及阻尼VSG的船舶光伏逆变器控制[J]. 计算机仿真, 2021, 38(1): 82-87.
[3] 郭森闯, 何皑, 肖波, 等. 一种基于神经网络的航改燃气轮机转速控制器[J]. 推进技术, 2023, 44(3): 205-217.
[4] AALREBEI O F, AL ASSAF A H, AMHAMED A, et al. Ammonia-hydrogen-air gas turbine cycle and control analyses[J]. International Journal of Hydrogen Energy, 2022, 47(13), 8603-8620.
[5] 刘建宝, 单帅杰, 秦昕昕. 基于改进遗传算法优化燃气轮发电机组转速控制的方法[J]. 海军工程大学学报, 2022, 34(4): 47-52,112.
[6] 张启航, 李学民, 祝存玺. 基于强化学习的燃气轮机转速控制策略研究[J]. 热能动力工程, 2022, 37(12): 148-156.
[7] 邓望权, 田震, 王子楠, 等. 基于PI与无模型自适应控制结合的燃气轮机转速控制方法[J]. 推进技术, 2022, 43(7): 399-407.
[8] 马树焕. 船舶燃气轮机转速自适应模糊控制[J]. 舰船科学技术, 2023, 45(22): 126-129.
MA S H. Adaptive fuzzy control of ship gas turbine speed[J]. Ship Science and Technology, 2022, 43(7): 399-407.
