论文标题

使用连续的自适应控制

Model-free Continuation of Periodic Orbits in Certain Nonlinear Systems Using Continuous-Time Adaptive Control

论文作者

Li, Yang, Dankowicz, Harry

论文摘要

本文概括了作者对非侵入性模型引用自适应控制设计的最新结果,用于基于控制的定期激发线性系统的定期轨道,与具有匹配的不确定性匹配的较大类别激发的非线性系统具有匹配的不确定性和已知结构。在未建模非线性的标量问题的情况下,还提出了候选自适应反馈设计。在前一种情况下,严格的分析显示了相关预测和估计错误的保证绩效界限。加上持续激发的假设,随后渐变响应是根据基于控制的持续范式所要求的先验未知的周期参考输入和独立于初始条件的独特确定的周期性响应。特别是,当参考输入等于寻求的周期性响应时,稳态控制输入就会消失。对于标量动力学的情况,具有未建模的非线性的情况下,尽管收敛速度缓慢。数值模拟验证了单个参数值的理论预测。与软件包可可的集成表明,沿稳定且不稳定的周期轨道的家族成功地延续了,参数调整最少。结果扩大了已知的无创反馈策略的信封,用于实验模型验证和工程设计。

This paper generalizes recent results by the authors on noninvasive model-reference adaptive control designs for control-based continuation of periodic orbits in periodically excited linear systems with matched uncertainties to a larger class of periodically excited nonlinear systems with matched uncertainties and known structure. A candidate adaptive feedback design is also proposed in the case of scalar problems with unmodeled nonlinearities. In the former case, rigorous analysis shows guaranteed performance bounds for the associated prediction and estimation errors. Together with an assumption of persistent excitation, there follows asymptotic convergence to periodic responses determined uniquely by an a priori unknown periodic reference input and independent of initial conditions, as required by the control-based continuation paradigm. In particular, when the reference input equals the sought periodic response, the steady-state control input vanishes. Identical conclusions follow for the case of scalar dynamics with unmodeled nonlinearities, albeit with slow rates of convergence. Numerical simulations validate the theoretical predictions for individual parameter values. Integration with the software package COCO demonstrate successful continuation along families of stable and unstable periodic orbits with a minimum of parameter tuning. The results expand the envelope of known noninvasive feedback strategies for use in experimental model validation and engineering design.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源