近壁面环境下UUV回收过程的自适应控制方法研究
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摘要
目前,随着世界范围内对海洋资源开发及海洋空间利用技术的不断探索,水下无人航行器UUV(Unmanned Underwater Vehicle)因为其具有作业模式灵活、隐蔽性高、安全性好等优点而引起各国工程人员越来越多的关注。当UUV完成任务后,或出现需要下载指令、上传数据或补充能源等情况时,UUV必须返回水下工作站。由于必须考虑UUV回收过程中隐蔽性、安全性及降低成本等方面的因素,UUV水下自主回收方式被越来越多地采用。本文采用平台搭载方式进行UUV水下自主回收,即在水下工作站背部为UUV设置专门的回收区域,该区域安装有短基线声呐、导引光源、锁紧装置等回收设施,UUV按照预先设计的控制和决策程序自主地坐落至该区域,并利用锁紧装置固定在水下工作站上,实现随艇而动,同时完成指令下载、数据传输或能源补充等工作。
UUV回收坐落过程是一个从无限宽广水域到近壁面受限水域的过程。坐落过程中UUV受到的水动力特性与宽广水域下相比发生变化,而且规律复杂,若仍以无限宽广水域下的UUV运动模型对所设计的控制器进行仿真来验证其性能的可靠性,这是没有说服力的。考虑到目前对于该问题仍没有相对成熟的理论做为依据,论文采用计算流体动力学软件Fluent对近壁面环境下UUV回收坐落过程中受到的水动力进行数值模拟计算,对计算所得到数据进行回归分析,总结出近壁面环境下,在UUV回收坐落过程中水动力随UUV高度不同的变化规律,并拟合出此过程的干扰计算公式,最后再根据UUV回收时的运动特点,建立采用平台搭载方法进行回收时的UUV六自由度运动模型。
由于UUV自身的非线性、弱观测、强耦合等特性,使UUV实现完全自主回收存在很多困难。采用传统的控制方法已经不能满足在复杂环境,尤其是在未知的近壁面环境下完成安全性和精确度都有很高要求的UUV水下自主回收,故本文采用自适应控制方法对UUV近壁面环境下自主回收过程的运动状态进行控制,这是因为自适应控制方法的特点在于它不仅能控制一个已知系统,还能控制一个完全或部分未知的系统,尤其适用于较为复杂的非线性系统。此外,本文还引入了非线性干扰观测器(DOB)作为控制回路的内环,它不仅能够有效补偿系统中的未知干扰,而且其内部的低通滤波器还可以消除由传感器引入的高频测量噪声对控制器的影响。
本文最后进行了UUV回收系统的半实物仿真,利用建立的UUV近壁面回收过程的运动模型,通过不同的水动力环境、水下工作站的不同运动方式以及是否加入高频测量噪声等仿真方案,对应用于控制UUV回收过程中垂直面运动的基于非线性干扰观测器的自适应控制方法性能进行验证,并将控制结果与单纯自适应控制方法和传统的PID控制方法进行比较,证明了UUV回收自适应控制器在未知环境下的鲁棒性、自校正能力、以及抑制高频噪声的能力。
With the development of ocean source exploitation and ocean space utilization, UUV (Unmanned Underwater Vehicle) has been paid more and more attention by engineers from all over the world. UUV must come back to the underwater workstation when assignments have been done, or it needs to download missions, transform data and charge up batteries. Automatic underwater recovery is used widely for the requirements of covert, safety and low cost. In this dissertation, flat-carrying recovery is adopted, that is a special location for UUV recovery is set on the back of the underwater workstation, where SBL (Short Base Line) sonar, guiding lights and fixed compartments are installed on. UUV comes down to the recovery location automatically according to the controllers and decision-making programs, which are decided in advance, and then the vehicle moves with the underwater workstation after being fixed to the flat. Meanwhile, mission download, data transforming and charging up are finished.
During the recovery, UUV comes down to the flat from infinite broad environment to near-wall region, that is, the characteristics of hydrodynamic change greatly, and the rule is so complex that it is not persuasive for the controller capability if simulating with the UUV motion model under infinite broad region. Considering no mature theory exists, "Fluent", a CFD (computational fluid dynamics) software, is used for numerical simulation calculating the hydrodynamic forces at different height in UUV recovery. Then the data coming from computing by Fluent is analyzed regressively, and the interference calculation formulas are fitted after the rules of the hydrodynamic are summarized. Finally, the 6-DOF model of UUV flat-carrying recovery is built based on the motion characteristics.
Considering the characteristics of nonlinear, weak-observation and strong couple, the automatic control of UUV is very difficult, so the traditional control method can not satisfy the automation performance under the complex environment, especially the unknown near-wall region. To deal with these problems, adaptive controller based on DOB (Nonlinear Disturbance Observer) is presented as an inner loop for UUV recovery. DOB not only can compensate the unknown inferences, but also eliminate the high frequency noise from sonar by the low pass filter in DOB.
At the end of this dissertation, some simulation schemes are simulated with the near wall UUV motion model. By comparing the simulation results with adaptive controller without DOB and PID controller, the performances of adaptive controller based on DOB for UUV recovery, such as robust, self-tuning, and high-frequency noise eliminating, are verified.
UUV回收坐落过程是一个从无限宽广水域到近壁面受限水域的过程。坐落过程中UUV受到的水动力特性与宽广水域下相比发生变化,而且规律复杂,若仍以无限宽广水域下的UUV运动模型对所设计的控制器进行仿真来验证其性能的可靠性,这是没有说服力的。考虑到目前对于该问题仍没有相对成熟的理论做为依据,论文采用计算流体动力学软件Fluent对近壁面环境下UUV回收坐落过程中受到的水动力进行数值模拟计算,对计算所得到数据进行回归分析,总结出近壁面环境下,在UUV回收坐落过程中水动力随UUV高度不同的变化规律,并拟合出此过程的干扰计算公式,最后再根据UUV回收时的运动特点,建立采用平台搭载方法进行回收时的UUV六自由度运动模型。
由于UUV自身的非线性、弱观测、强耦合等特性,使UUV实现完全自主回收存在很多困难。采用传统的控制方法已经不能满足在复杂环境,尤其是在未知的近壁面环境下完成安全性和精确度都有很高要求的UUV水下自主回收,故本文采用自适应控制方法对UUV近壁面环境下自主回收过程的运动状态进行控制,这是因为自适应控制方法的特点在于它不仅能控制一个已知系统,还能控制一个完全或部分未知的系统,尤其适用于较为复杂的非线性系统。此外,本文还引入了非线性干扰观测器(DOB)作为控制回路的内环,它不仅能够有效补偿系统中的未知干扰,而且其内部的低通滤波器还可以消除由传感器引入的高频测量噪声对控制器的影响。
本文最后进行了UUV回收系统的半实物仿真,利用建立的UUV近壁面回收过程的运动模型,通过不同的水动力环境、水下工作站的不同运动方式以及是否加入高频测量噪声等仿真方案,对应用于控制UUV回收过程中垂直面运动的基于非线性干扰观测器的自适应控制方法性能进行验证,并将控制结果与单纯自适应控制方法和传统的PID控制方法进行比较,证明了UUV回收自适应控制器在未知环境下的鲁棒性、自校正能力、以及抑制高频噪声的能力。
With the development of ocean source exploitation and ocean space utilization, UUV (Unmanned Underwater Vehicle) has been paid more and more attention by engineers from all over the world. UUV must come back to the underwater workstation when assignments have been done, or it needs to download missions, transform data and charge up batteries. Automatic underwater recovery is used widely for the requirements of covert, safety and low cost. In this dissertation, flat-carrying recovery is adopted, that is a special location for UUV recovery is set on the back of the underwater workstation, where SBL (Short Base Line) sonar, guiding lights and fixed compartments are installed on. UUV comes down to the recovery location automatically according to the controllers and decision-making programs, which are decided in advance, and then the vehicle moves with the underwater workstation after being fixed to the flat. Meanwhile, mission download, data transforming and charging up are finished.
During the recovery, UUV comes down to the flat from infinite broad environment to near-wall region, that is, the characteristics of hydrodynamic change greatly, and the rule is so complex that it is not persuasive for the controller capability if simulating with the UUV motion model under infinite broad region. Considering no mature theory exists, "Fluent", a CFD (computational fluid dynamics) software, is used for numerical simulation calculating the hydrodynamic forces at different height in UUV recovery. Then the data coming from computing by Fluent is analyzed regressively, and the interference calculation formulas are fitted after the rules of the hydrodynamic are summarized. Finally, the 6-DOF model of UUV flat-carrying recovery is built based on the motion characteristics.
Considering the characteristics of nonlinear, weak-observation and strong couple, the automatic control of UUV is very difficult, so the traditional control method can not satisfy the automation performance under the complex environment, especially the unknown near-wall region. To deal with these problems, adaptive controller based on DOB (Nonlinear Disturbance Observer) is presented as an inner loop for UUV recovery. DOB not only can compensate the unknown inferences, but also eliminate the high frequency noise from sonar by the low pass filter in DOB.
At the end of this dissertation, some simulation schemes are simulated with the near wall UUV motion model. By comparing the simulation results with adaptive controller without DOB and PID controller, the performances of adaptive controller based on DOB for UUV recovery, such as robust, self-tuning, and high-frequency noise eliminating, are verified.
引文
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