基于非线性动力学模型的多旋翼避碰预测控制稀疏辨识

IF 2.3 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Jayden Dongwoo Lee, Youngjae Kim, Yoonseong Kim, Hyochoong Bang
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引用次数: 0

摘要

本文提出了一种考虑载荷不确定性和未知动力学的多旋翼避碰数据驱动模型预测控制(MPC)方法。为了解决这一问题,采用非线性动力学稀疏辨识(SINDy)方法推导了多转子系统的控制方程。SINDy能够从有限的数据中发现目标系统的方程,假设几个主导函数主要表征系统的行为。此外,提出了一种将基线控制器与MPC相结合的数据收集框架,以生成用于模型识别的多种轨迹。利用多旋翼动力学的先验知识和归一化技术,利用候选函数库来提高基于sindy的模型的精度。MPC利用SINDy的数据驱动模型,在满足状态约束和输入约束(包括避障约束)的情况下,实现精确的轨迹跟踪。仿真结果表明,在考虑质量参数不确定性和气动影响的情况下,SINDy能够成功辨识多旋翼系统的控制方程。结果表明,该方法在避障性能和轨迹跟踪性能上均优于参数不确定性和未知气动模型的传统MPC方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Sparse Identification of Nonlinear Dynamics-Based Model Predictive Control for Multirotor Collision Avoidance

Sparse Identification of Nonlinear Dynamics-Based Model Predictive Control for Multirotor Collision Avoidance

This article proposes a data-driven model predictive control (MPC) method for multirotor collision avoidance, considering uncertainties and the unknown dynamics caused by a payload. To address this challenge, sparse identification of nonlinear dynamics (SINDy) is employed to derive the governing equations of the multirotor system. SINDy is capable of discovering the equations of target systems from limited data, under the assumption that a few dominant functions primarily characterize the system's behavior. In addition, a data collection framework that combines a baseline controller with MPC is proposed to generate diverse trajectories for model identification. A candidate function library, informed by prior knowledge of multirotor dynamics, along with a normalization technique, is utilized to enhance the accuracy of the SINDy-based model. Using data-driven model from SINDy, MPC is used to achieve accurate trajectory tracking while satisfying state and input constraints, including those for obstacle avoidance. Simulation results demonstrate that SINDy can successfully identify the governing equations of the multirotor system, accounting for mass parameter uncertainties and aerodynamic effects. Furthermore, the results confirm that the proposed method outperforms conventional MPC, which suffers from parameter uncertainty and an unknown aerodynamic model, in both obstacle avoidance and trajectory tracking performance.

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来源期刊
IET Control Theory and Applications
IET Control Theory and Applications 工程技术-工程:电子与电气
CiteScore
5.70
自引率
7.70%
发文量
167
审稿时长
5.1 months
期刊介绍: IET Control Theory & Applications is devoted to control systems in the broadest sense, covering new theoretical results and the applications of new and established control methods. Among the topics of interest are system modelling, identification and simulation, the analysis and design of control systems (including computer-aided design), and practical implementation. The scope encompasses technological, economic, physiological (biomedical) and other systems, including man-machine interfaces. Most of the papers published deal with original work from industrial and government laboratories and universities, but subject reviews and tutorial expositions of current methods are welcomed. Correspondence discussing published papers is also welcomed. Applications papers need not necessarily involve new theory. Papers which describe new realisations of established methods, or control techniques applied in a novel situation, or practical studies which compare various designs, would be of interest. Of particular value are theoretical papers which discuss the applicability of new work or applications which engender new theoretical applications.
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