| 基于有限时间扰动观测器的水下机器人路径规划非线性模型预测控制方法 |
投稿时间：2025-09-18 修订日期：2025-12-08  点此下载全文 |
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| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目） |
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| 中文摘要:针对自主水下机器人（AUV）在复杂扰动环境下路径规划与避障能力不足的问题，本文提出一种融合有限时间扰动观测器（FTDO）与非线性模型预测控制（NMPC）的路径规划控制方法。首先，基于AUV特性引入运动学与动力学约束，根据动力定位原理建立AUV的三自由度状态空间模型。其次，为抑制环境扰动带来的不确定性，设计FTDO实现扰动的快速估计与补偿，提高系统的鲁棒性与稳定性。在此基础上，结合NMPC构建优化控制器，实现路径规划与避障控制的有机统一。仿真结果验证了所提方法在路径规划精度与抗干扰方面的有效性，与NMPC和SMC控制器相比，跟踪误差控制精度提升26.6%和14.7%。 |
| 中文关键词:自主水下机器人 非线性模型预测控制 有限时间扰动观测器 |
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| Nonlinear model predictive control method for path planning of underwater vehicle based on finite-time disturbance observer |
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| Abstract:Aiming at the insufficient path planning and obstacle avoidance capabilities of Autonomous Underwater Vehicle (AUV) in complex disturbance environments, this paper proposes a path planning and control method integrating a Finite Time Disturbance Observer (FTDO) with Nonlinear Model Predictive Control (NMPC). Firstly, kinematic and dynamic constraints are introduced based on the characteristics of AUV., and a three-degree-of-freedom state-space model of the AUV is established according to dynamic positioning principles. Secondly, to suppress uncertainties caused by environmental disturbances, an FTDO is designed to achieve rapid disturbance estimation and compensation, enhancing the system’s robustness and stability. On this basis, an optimized controller is constructed by combining NMPC, realizing the organic integration of path planning and obstacle avoidance control. The simulation results validate the effectiveness of the proposed method in terms of path planning accuracy and disturbance rejection. Compared to NMPC and SMC controllers, the tracking error control accuracy is improved by 26.6% and 14.7%, respectively. |
| keywords:Autonomous underwater vehicle Nonlinear model predictive control finite-time disturbance observer |
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