Adjoint-Based Projections for Uncertainty Quantification near Stochastically Perturbed Limit Cycles and Tori
Zaid Ahsan, Harry Dankowicz, Christian Kuehn

TL;DR
This paper introduces a novel boundary-value problem approach using adjoints to quantify uncertainty near stable limit cycles and tori in dynamical systems, improving accuracy and providing explicit solutions.
Contribution
It develops a new formulation for uncertainty quantification near limit cycles and tori, with explicit covariance solutions and enhanced analysis techniques.
Findings
Explicit covariance solutions for limit cycles and tori.
Validation against numerical simulations confirms accuracy.
Application to a 4D system demonstrates practical utility.
Abstract
This paper presents a new boundary-value problem formulation for quantifying uncertainty induced by the presence of small Brownian noise near transversally stable periodic orbits (limit cycles) and quasiperiodic invariant tori of the deterministic dynamical systems obtained in the absence of noise. The formulation uses adjoints to construct a continuous family of transversal hyperplanes that are invariant under the linearized deterministic flow near the limit cycle or quasiperiodic invariant torus. The intersections with each hyperplane of stochastic trajectories that remain near the deterministic cycle or torus over intermediate times may be approximated by a Gaussian distribution whose covariance matrix can be obtained from the solution to the corresponding boundary-value problem. In the case of limit cycles, the analysis improves upon results in the literature through the explicit…
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Taxonomy
TopicsProbabilistic and Robust Engineering Design · Advanced Multi-Objective Optimization Algorithms
