复杂海洋环境下水下异构多自治机器人系统的协调控制

Complex ocean current, low communication data rate, narrow bandwidth of underwater acoustic communication, system parameter uncertainty, system heterogeneity, and limited energy of AUVs (Autonomous Underwater Vehicles) will bring great challenges to the cooperative control of multi-AUV systems. This project aims to present some effective control methods to solve the cooperative control problems of multi-AUV systems under above constraints, and improve the anti- jamming ability, system control reliability, and life of multi-AUV systems. Firstly, the complex ocean current can be decomposed into modeled disturbances and unknown disturbances. We will investigate methods of modeled disturbance rejecting and unknown disturbance restrain, and present a general framework based on output regulation theory for output consensus of heterogeneous multi-AUV systems under complex ocean current. Then, we consider the topology uncertainty induced by communication constraints such as time delays and data dropouts, and investigate robust adaptive control methods to design control gains such that they will be independent of the Laplacian matrix of system topology, which is global of nature and hard to obtain in the case that system topology is unknown. Simultaneously, we also consider the uncertainties of system parameters, and investigate the robust controllers for the heterogeneous multi-AUV systems based on robust output regulation theory such that the disturbances can be dynamically compensated. Thirdly, based on the output consensus theory proposed in this project, we further consider the narrow bandwidth of underwater acoustic communication and limited energy of AUV, and try to develop novel low-energy control techniques based on measurement output feedback and event-triggered control techniques. At last, an experiment platform will be build to test the proposed results in this project. The outcome of this project will greatly promote the technical innovation in sea explorations, underwater sensor networking, marine surveys, and so on.

海洋监测任务多样性、复杂洋流干扰、水声通信低速率和窄带宽、系统模型参数不确定以及有限的能量等因素为水下机器人的协调控制带来了巨大挑战。本项目旨在解决异构水下机器人系统在复杂海洋环境下的协调控制问题，提高系统的抗干扰能力、可靠性和自持力。首先，针对复杂洋流干扰，研究可建模干扰的消除和未知干扰的抑制方法，建立基于输出调节理论的异构水下机器人系统输出一致性协议框架。其次，综合考虑通信约束带来的拓扑不确定性和系统参数不确定性，分别采用鲁棒自适应控制方法和基于内模原理的输出调节控制器设计，实现控制增益的自适应调节以及参数不确定系统的干扰动态补偿。进一步考虑水声通信带宽窄的特点以及提高系统自持力的需求，采用基于测量输出反馈的方法和事件触发控制器设计来降低控制信息的传输维数同时减少实现编队控制的通信能耗。最后，建立实际海洋环境下的水下异构机器人实验平台，为本项目提供技术支撑和应用原型。

本项目旨在研究复杂干扰、通信约束以及系统模型不确定的异构非线性网络化系统的协调控制，以期应用于解决多水下机器人系统在复杂洋流、窄带宽水声通信、负责动力学模型等影响下的协同运动控制问题。为此，本项目开展了如下研究内容：首先，研究可建模干扰的消除和未知干扰的抑制方法，建立基于输出调节理论的异构非线性网络化系统输出一致性协议框架。其次，综合考虑通信约束带来的拓扑不确定性和系统参数不确定性，分别采用鲁棒自适应控制方法和基于内模原理的输出调节控制器设计，实现控制增益的自适应调节以及参数不确定系统的干扰动态补偿。进一步考虑水声通信带宽窄的特点以及提高系统自持力的需求，采用基于测量输出反馈的方法和事件触发控制器设计来降低控制信息的传输维数同时减少实现编队控制的通信能耗。最后，建立水下机器人实验平台，为本项目提供技术支撑和应用原型。本项目从理论层面提出了基于内模原理的鲁棒控制方法、基于调节方程近似解的自适应一致性协议、有限时间一致性控制、基于事件促发机制的一致性协议等新型控制方法，很好地解决了干扰、随机动态、参数不确定性等影响下的异构非线性网络化系统的协调控制问题，并初步建成实现定位、轨迹规划、鲁棒控制等功能的水下机器人实验平台。本项目的研究成果将为进一步深入研究水下机器人的动态组网和智能控制奠定坚实基础。