论文标题
使用平方之和放松的多项式系统的学习控制
Learning control for polynomial systems using sum of squares relaxations
论文作者
论文摘要
本文直接从数据中直接从数据中考虑了非线性多项式系统的学习控制定律的问题，这些数据是在有限的时间段内在实验中收集的输入输出测量。在没有明确识别系统动力学的情况下，仅使用实验数据直接为非线性多项式系统设计了稳定定律。通过使用基于数据的平方编程总和，可以构建稳定状态依赖性控制收益。
This paper considers the problem of learning control laws for nonlinear polynomial systems directly from the data, which are input-output measurements collected in an experiment over a finite time period. Without explicitly identifying the system dynamics, stabilizing laws are directly designed for nonlinear polynomial systems using experimental data alone. By using data-based sum of square programming, the stabilizing state-dependent control gains can be constructed.
