半潜式深海平台动力定位系统推力.docx
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半潜式深海平台动力定位系统推力,摘要随着工业的飞跃发展，人类对于能源的需求消耗越来越多，陆地和近海领域能源被开采殆尽，而深海领域蕴藏着丰富的资源，深海钻井平台在这种背景下应运而生。面对深海复杂的海况钻井平台要保持其定位精度以完成采油任务，传统的锚泊技术已经无法满足深海作业的定位要求，越来越多的海洋平台采用动力定位系统。动力定位系统利用自身推进器产生的...
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摘 要
随着工业的飞跃发展，人类对于能源的需求消耗越来越多，陆地和近海领域能源被开采殆尽，而深海领域蕴藏着丰富的资源，深海钻井平台在这种背景下应运而生。面对深海复杂的海况钻井平台要保持其定位精度以完成采油任务，传统的锚泊技术已经无法满足深海作业的定位要求，越来越多的海洋平台采用动力定位系统。
动力定位系统利用自身推进器产生的推力，有效产生力矩和反力矩以抗衡外界力和力矩以保持平台定位。推力分配问题实质上是求解非线性方程组最优解的问题，即在满足一定的约束条件基础上，在众多组合中寻找每个推进器最适当的推力幅值和方向，使其达到推进系统能耗最优和误差最优的目标。本文以半潜式深海平台为研究对象，主要对推力分配策略进行研究和比较。
首先针对钻井平台具体对象，对外界风浪流载荷、平台运动模型等进行分析。同时根据半潜式海洋平台的动力定位系统的特殊性，阐述深海钻井平台推进器的选型、布置并分析其原因，并描述推进器与平台之间的推力特性。
然后结合半潜式深海平台推进器配置方案，重点分析在此配置方案下的推力分配策略。采用序列二次规划法进行推力最优分配，推力分配目标旨在最小化推力系统的能耗和推力误差，同时考虑推进器的推力区域、推力极限等约束，并实现对推力区域的线性化处理，通过仿真结果指出序列二次规划算法的不足，其对初值的依赖性强，结果不稳定，易陷入局部最优。
最后根据动力定位系统推力系统的基本要求，以及推力分配问题在近年来研究现状，深入了解比较各种优化算法的优劣，在此基础上提出基于量子粒子群算法的推力分配策略，并采用量子粒子群算法制定了详尽的办法解决推力分配问题。在相同的推力指令要求下，分别基于能耗最优和误差最优两种不同的海况要求，比较两种算法的推力分配结果并分析。仿真结果表明量子粒子群算法具有更好的寻优结果，但寻优时间相对序列二次规划法长，所以对于量子粒子群算法应用于工程应用还需要进一步改进。
关键词 动力定位系统；推力分配；序列二次规划法；量子粒子群算法；
Abstract
With the development of industry in the world, more and more resources are required and consumed. As a result, resources on land and the sea close to the shore will be mined out in the near future. There are extraordinary abundant resources in the deep sea, so deepwater drilling platform arises at the historic moment. How to operate the drilling platform in the complex deepwater surroundings to fulfill drilling cannot afford to ignore. Traditional way to anchor the platforms cannot meet the orientation require in the deepwater surroundings. More and more drilling rigs have adopted dynamic positioning system (DPS).
Compared to the traditional way to anchor the platforms, DPS totally depends on its own thrust system to generate force and moment to orient the drilling rig. Thrust allocation is defined to search the best thrust of every propeller in order to meet the objective, such as minimize the energy and thrust error, by using the platform’s own propellers. Also the thrust must satisfy some restriction.
Firstly according to the particularity of the dynamic positioning system, the selection and arrangement of the propellers on the drilling rig is expatiated and the reason is explained as well. What’s more, the thrust characteristics of the propeller are depicted. Integrating the semi-submersible offshore platform’s thruster configuration scheme of this topic, the thrust allocation problem in this case is focused on the analysis. Semi-submersible drilling rigs in this thesis possess eight azimuth propellers. The objective of thrust allocation is to minimize the energy consumption of thrust system and the thrust error, considering the restriction such as the limit of the propellers and singularity and so on. This thesis adopted SQP (Sequence quadratic programming) to solve the optimal solution of thrust allocation at first. The shortcomings using SQP methods are illustrated, for example, it strongly depends on the initial value and is easy to fall into the local optimum. Then by means of analyzing the essential request and the development of the thrust allocation, and in-depth understanding on the various kinds of optimization algorithms, based on which, this thesis put forward a new method using QPSO (Quantum particle swarm optimization) method to solve the thrust allocation. Then QPSO combined with disjunctive programming techniques are used to present a more elaborate solution to optimal thrust allocation problems. The simulation results showed that the method using QPSO possess good effect to search for the optimal result for the thrust allocation at last.
Keywords: Dynamic position system; thrust allocation; Sequence quadratic programming; Quantum particle swarm optimization.
目录
摘 要 I
Abstract III
第1章 绪论 1
1.1 课题研究背景及意义 1
1.2 半潜式平台及其动力定位系统 2
1.3 国内外推力分配算法研究现状 5
1.4 量子粒子群算法的发展及其优点 6
1.5 本论文主要研究内容 7
第2章 半潜式平台动力定位系统数学建模 10
2.1 半潜式深海平台主要参数 10
2.2 环境载荷模型 11
2.2.1 风载荷 11
2.2.2 流载荷 13
2.2.3 波浪二阶力 14
2.3 半潜式钻井平台的数学模型 14
2.3.1 平台运动模型 14
2.3.2 平台控制模型 15
2.3.3 Matlab模型仿真 17
2.4 本章小结 19
第3章 半潜式钻井平..
随着工业的飞跃发展，人类对于能源的需求消耗越来越多，陆地和近海领域能源被开采殆尽，而深海领域蕴藏着丰富的资源，深海钻井平台在这种背景下应运而生。面对深海复杂的海况钻井平台要保持其定位精度以完成采油任务，传统的锚泊技术已经无法满足深海作业的定位要求，越来越多的海洋平台采用动力定位系统。
动力定位系统利用自身推进器产生的推力，有效产生力矩和反力矩以抗衡外界力和力矩以保持平台定位。推力分配问题实质上是求解非线性方程组最优解的问题，即在满足一定的约束条件基础上，在众多组合中寻找每个推进器最适当的推力幅值和方向，使其达到推进系统能耗最优和误差最优的目标。本文以半潜式深海平台为研究对象，主要对推力分配策略进行研究和比较。
首先针对钻井平台具体对象，对外界风浪流载荷、平台运动模型等进行分析。同时根据半潜式海洋平台的动力定位系统的特殊性，阐述深海钻井平台推进器的选型、布置并分析其原因，并描述推进器与平台之间的推力特性。
然后结合半潜式深海平台推进器配置方案，重点分析在此配置方案下的推力分配策略。采用序列二次规划法进行推力最优分配，推力分配目标旨在最小化推力系统的能耗和推力误差，同时考虑推进器的推力区域、推力极限等约束，并实现对推力区域的线性化处理，通过仿真结果指出序列二次规划算法的不足，其对初值的依赖性强，结果不稳定，易陷入局部最优。
最后根据动力定位系统推力系统的基本要求，以及推力分配问题在近年来研究现状，深入了解比较各种优化算法的优劣，在此基础上提出基于量子粒子群算法的推力分配策略，并采用量子粒子群算法制定了详尽的办法解决推力分配问题。在相同的推力指令要求下，分别基于能耗最优和误差最优两种不同的海况要求，比较两种算法的推力分配结果并分析。仿真结果表明量子粒子群算法具有更好的寻优结果，但寻优时间相对序列二次规划法长，所以对于量子粒子群算法应用于工程应用还需要进一步改进。
关键词 动力定位系统；推力分配；序列二次规划法；量子粒子群算法；
Abstract
With the development of industry in the world, more and more resources are required and consumed. As a result, resources on land and the sea close to the shore will be mined out in the near future. There are extraordinary abundant resources in the deep sea, so deepwater drilling platform arises at the historic moment. How to operate the drilling platform in the complex deepwater surroundings to fulfill drilling cannot afford to ignore. Traditional way to anchor the platforms cannot meet the orientation require in the deepwater surroundings. More and more drilling rigs have adopted dynamic positioning system (DPS).
Compared to the traditional way to anchor the platforms, DPS totally depends on its own thrust system to generate force and moment to orient the drilling rig. Thrust allocation is defined to search the best thrust of every propeller in order to meet the objective, such as minimize the energy and thrust error, by using the platform’s own propellers. Also the thrust must satisfy some restriction.
Firstly according to the particularity of the dynamic positioning system, the selection and arrangement of the propellers on the drilling rig is expatiated and the reason is explained as well. What’s more, the thrust characteristics of the propeller are depicted. Integrating the semi-submersible offshore platform’s thruster configuration scheme of this topic, the thrust allocation problem in this case is focused on the analysis. Semi-submersible drilling rigs in this thesis possess eight azimuth propellers. The objective of thrust allocation is to minimize the energy consumption of thrust system and the thrust error, considering the restriction such as the limit of the propellers and singularity and so on. This thesis adopted SQP (Sequence quadratic programming) to solve the optimal solution of thrust allocation at first. The shortcomings using SQP methods are illustrated, for example, it strongly depends on the initial value and is easy to fall into the local optimum. Then by means of analyzing the essential request and the development of the thrust allocation, and in-depth understanding on the various kinds of optimization algorithms, based on which, this thesis put forward a new method using QPSO (Quantum particle swarm optimization) method to solve the thrust allocation. Then QPSO combined with disjunctive programming techniques are used to present a more elaborate solution to optimal thrust allocation problems. The simulation results showed that the method using QPSO possess good effect to search for the optimal result for the thrust allocation at last.
Keywords: Dynamic position system; thrust allocation; Sequence quadratic programming; Quantum particle swarm optimization.
目录
摘 要 I
Abstract III
第1章 绪论 1
1.1 课题研究背景及意义 1
1.2 半潜式平台及其动力定位系统 2
1.3 国内外推力分配算法研究现状 5
1.4 量子粒子群算法的发展及其优点 6
1.5 本论文主要研究内容 7
第2章 半潜式平台动力定位系统数学建模 10
2.1 半潜式深海平台主要参数 10
2.2 环境载荷模型 11
2.2.1 风载荷 11
2.2.2 流载荷 13
2.2.3 波浪二阶力 14
2.3 半潜式钻井平台的数学模型 14
2.3.1 平台运动模型 14
2.3.2 平台控制模型 15
2.3.3 Matlab模型仿真 17
2.4 本章小结 19
第3章 半潜式钻井平..
