快速收敛非线性微分器
Rapid-convergent nonlinear differentiator
AI总结：
提出一种基于奇异摄动技术的快速收敛非线性微分器，通过引入连续幂函数和线性校正项减少抖振、改善动态性能，并集成非线性项与线性滤波器增强鲁棒性。
摘要：
提出一种适用于快速收敛的非线性微分器，基于奇异摄动技术。该微分器设计不仅通过引入连续幂函数充分减少导数估计的抖振现象，而且通过在线性项中加入非线性校正项改善动态性能。此外，通过集成非线性项和线性滤波器获得了强鲁棒性。快速收敛微分器的优点包括优异的动态性能、充分抑制噪声、避免抖振现象以及不依赖于系统模型。理论结果通过计算机仿真和实验得到验证。
英文摘要：
A nonlinear differentiator being fit for rapid convergence is presented, which is based on singular perturbation technique. The differentiator design can not only sufficiently reduce the chattering phenomenon of derivative estimation by introducing a continuous power function, but the dynamical performances are also improved by adding linear correction terms to the nonlinear ones. Moreover, strong robustness ability is obtained by integrating nonlinear items and the linear filter. The merits of the rapid-convergent differentiator include the excellent dynamical performances, restraining noises sufficiently, avoiding the chattering phenomenon and being not based on system model. The theoretical results are confirmed by computer simulations and an experiment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
