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Trajectory-based robustness analysis for nonlinear systems
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DOI：10.1002/rnc.7009.png)
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Abstract
En 中文
This article considers the robustness of an uncertain nonlinear system along a finite-horizon trajectory. The uncertain system is modeled as a connection of a nonlinear system and a perturbation. The analysis relies on three ingredients. First, the nonlinear system is approximated by a linear time-varying (LTV) system via linearization along a trajectory. This linearization introduces an additional forcing input due to the nominal trajectory. Second, the input/output behavior of the perturbation is described by time-domain, integral quadratic constraints (IQCs). Third, a dissipation inequality is formulated to bound the worst-case deviation of an output signal due to the uncertainty. These steps yield a differential linear matrix inequality (DLMI) condition to bound the worst-case performance. The robustness condition is then converted to an equivalent condition in terms of a Riccati differential equation. This yields a computational method that avoids heuristics often used to solve DLMIs, for example, time gridding. The approach is demonstrated by a two-link robotic arm example.
Keywords:
linearization
nonlinear systems
robustness
uncertainty
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3.2
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