微小型水下机器人运动控制及可靠性研究
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摘要
微小型化是未来水下机器人的一个重要发展方向。由于具有体积小、机动灵活、成本低、搭载方便的特点,微小型水下机器人可用于海洋探测与资源开发中的复杂海洋环境下的各种水下观测、水下作业等任务,是海洋探测与资源开发系统装备中的重要组成部分。在微小型水下机器人的研究和开发中,舵、翼、桨联合操纵的微小型水下机器人的运动控制以及可靠性技术是急需发展和完善的技术。
论文以某微小型水下机器人为研究对象,首先建立了运动仿真模型,重点讨论了舵、翼有效作用的解算过程,并构建了具有半实物仿真功能的运动仿真系统。讨论了水下机器人PDCE运动控制系统体系结构及其主要组成部分。在充分考虑水下机器人运动能力的基础上建立目标指令解释单元以获得可直接执行的目标指令。详细讨论了舵、翼、桨联合操纵的推力分配方式,采用水下机器人纵倾控制和速度控制联合操纵的方法,实现深度控制。由于微小型水下机器人尺度小,施力装置少,其运动属于欠自由度,因此在控制方法上采用改进的粒子群优化算法对S面控制器进行了参数寻优,取得良好效果。提出广义S型模糊神经网络控制方法来提高微小型水下机器人的机动性和反应能力,试验验证了所提出控制方法的可行性和优越性。最后,对运动控制系统进行了可靠性评估和分析。提出基于Bayes思想的可靠性综合评估方法对控制系统进行可靠性评估,采用故障树分析法对控制系统进行可靠性分析来评价控制系统的可靠性水平,分析系统各组成部分的薄弱环节,提出了改进建议。
Miniaturization is one important direction for autonomous underwater vehicles in the future. Due to small volume, excellent maneuverability and invisibility, low energy consumption, low resistance, high ability to avoid obstacles, there is a good prospect for Mini autonomous underwater vehicles (mini-AUVs) in the fields of military communication, marine mining and expedition and so on. For mini-AUVs with fins, the research on motion control and reliability is needed be developed and perfected.
In this thesis, the research object is certain mini-AUV. Firstly, we build the motion model in six-degree freedom and analyze the force and hydrodynamic coefficients, especially the fin effective action, and the simulation system with semi physical function is established. PDCE motion control system architecture for the AUVs and the ingredients are discussed in detailed. The unit of object order explanation is proposed based on considering thoroughly motion ability of the mini-AUVs, and the object orders which can be carried out directly are obtained. The force allocation function based on rudder-wing-propeller polar control is introduced, so we adopt pitch and velocity control to achieve depth control. Owing to small size and few force devices, motion control of the mini-AUVs is lacking-freedom control. So we propose improved particle swarm optimization (PSO) to optimize the parameters of S surface control, and the performance is satisfied. Moreover, we propose a novel control method bases on generalized sigmoid fuzzy neural network (SFNN) to improve the maneuverability and the ability to avoid obstacles. The experiment results verify the feasibility and superiority. Finally, reliability evaluation and reliability analysis are carried out for the motion control system. General evaluation method based on Bayes thought is proposed carried out reliability evaluation. Fault tree analysis is introduced to carry out reliability analysis to evaluate the reliability level of the motion control system and analyze the weakness of each ingredients, so we can give some improved advice.
论文以某微小型水下机器人为研究对象,首先建立了运动仿真模型,重点讨论了舵、翼有效作用的解算过程,并构建了具有半实物仿真功能的运动仿真系统。讨论了水下机器人PDCE运动控制系统体系结构及其主要组成部分。在充分考虑水下机器人运动能力的基础上建立目标指令解释单元以获得可直接执行的目标指令。详细讨论了舵、翼、桨联合操纵的推力分配方式,采用水下机器人纵倾控制和速度控制联合操纵的方法,实现深度控制。由于微小型水下机器人尺度小,施力装置少,其运动属于欠自由度,因此在控制方法上采用改进的粒子群优化算法对S面控制器进行了参数寻优,取得良好效果。提出广义S型模糊神经网络控制方法来提高微小型水下机器人的机动性和反应能力,试验验证了所提出控制方法的可行性和优越性。最后,对运动控制系统进行了可靠性评估和分析。提出基于Bayes思想的可靠性综合评估方法对控制系统进行可靠性评估,采用故障树分析法对控制系统进行可靠性分析来评价控制系统的可靠性水平,分析系统各组成部分的薄弱环节,提出了改进建议。
Miniaturization is one important direction for autonomous underwater vehicles in the future. Due to small volume, excellent maneuverability and invisibility, low energy consumption, low resistance, high ability to avoid obstacles, there is a good prospect for Mini autonomous underwater vehicles (mini-AUVs) in the fields of military communication, marine mining and expedition and so on. For mini-AUVs with fins, the research on motion control and reliability is needed be developed and perfected.
In this thesis, the research object is certain mini-AUV. Firstly, we build the motion model in six-degree freedom and analyze the force and hydrodynamic coefficients, especially the fin effective action, and the simulation system with semi physical function is established. PDCE motion control system architecture for the AUVs and the ingredients are discussed in detailed. The unit of object order explanation is proposed based on considering thoroughly motion ability of the mini-AUVs, and the object orders which can be carried out directly are obtained. The force allocation function based on rudder-wing-propeller polar control is introduced, so we adopt pitch and velocity control to achieve depth control. Owing to small size and few force devices, motion control of the mini-AUVs is lacking-freedom control. So we propose improved particle swarm optimization (PSO) to optimize the parameters of S surface control, and the performance is satisfied. Moreover, we propose a novel control method bases on generalized sigmoid fuzzy neural network (SFNN) to improve the maneuverability and the ability to avoid obstacles. The experiment results verify the feasibility and superiority. Finally, reliability evaluation and reliability analysis are carried out for the motion control system. General evaluation method based on Bayes thought is proposed carried out reliability evaluation. Fault tree analysis is introduced to carry out reliability analysis to evaluate the reliability level of the motion control system and analyze the weakness of each ingredients, so we can give some improved advice.
引文
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