部分测量下非线性系统稳态前馈输入的数据驱动设计
Data-driven design of steady-state feedforward inputs for nonlinear systems under partial measurement
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中文总结 AI 辅助
本文提出一种数据驱动控制框架，利用输入输出数据替代精确模型，结合内模原理与非线性分析，提升非线性系统轨迹跟踪控制器设计的可处理性，并在机械负载和电液执行器上验证有效性。
中文摘要 AI 辅助
为非线性系统设计轨迹跟踪控制器仍然是一个重大挑战，传统上需要精确的数学模型和复杂的解析推导。虽然内模原理（IMP）为此类问题提供了坚实的理论基础，但其应用常常受到模型不确定性和非线性控制器综合固有复杂性的阻碍。本文提出了一种实用的数据驱动控制框架，通过利用原始输入输出数据，绕过了对显式第一性原理模型的需求。通过将内模原理理论的基本结果与非线性系统分析相结合，所提出的方法提高了设计的可处理性。该框架的有效性通过在两个不同的非线性平台上的数值模拟得到验证：一个具有非线性摩擦项的机械负载和一个电液执行器系统。
英文摘要
Designing trajectory tracking controllers for nonlinear systems remains a significant challenge, traditionally requiring precise mathematical models and complex analytical derivations. While the Internal Model Principle (IMP) provides a robust theoretical foundation for such problems, its application is often hindered by model uncertainty and the inherent complexity of nonlinear controller synthesis. This work proposes a practical data-driven control framework that bypasses the need for an explicit first-principles model by utilizing raw input-output data. By integrating fundamental results from IMP theory with nonlinear system analysis, the proposed approach improves design tractability. The framework's efficacy is validated through numerical simulations on two distinct nonlinear platforms: a mechanical load with a nonlinear friction term and an electrohydraulic actuator system.
发表机构
- University of Minnesota-Twin Cities（明尼苏达大学双城分校）
- DEVCOM Army Research Laboratory（德弗科姆陆军研究实验室）
机构由 AI 辅助整理，请以论文原文为准。
