Adjoint-based Hopf-bifurcation Instability Suppression via First Lyapunov Coefficient

TL;DR

This paper introduces an adjoint-based method to efficiently compute derivatives of the first Lyapunov coefficient, enabling stability-constrained optimization to suppress unstable Hopf bifurcations in complex engineering systems.

Contribution

It develops an accurate, scalable adjoint method leveraging reverse algorithmic differentiation for computing Lyapunov coefficient derivatives in bifurcation analysis.

Findings

Effective suppression of unstable bifurcations demonstrated in three models.

The method shows high accuracy and efficiency in large-scale nonlinear problems.

Potential for broad application in aeroelastic and aerodynamic optimization.

Abstract

Many physical systems exhibit limit cycle oscillations induced by Hopf bifurcations. In aerospace engineering, limit cycle oscillations arise from undesirable Hopf bifurcation phenomena such as aeroelastic flutter and transonic buffet. In some cases, the resulting limit cycle oscillations can themselves be unstable, leading to amplitude divergence or hysteretic transitions that threaten structural integrity and performance. Avoiding such phenomena when performing gradient based design optimization requires a constraint that quantifies the stability of the bifurcations and the derivative of that constraint with respect to the design variables. To capture the local stability of bifurcations, we leverage the first Lyapunov coefficient, which predicts whether the resulting limit cycle oscillation is stable or unstable. We develop an accurate and efficient method for computing derivatives of the first Lyapunov coefficient. We leverage the adjoint method and reverse algorithmic differentiation to efficiently compute the derivative of the first Lyapunov coefficient. We demonstrate the efficacy of the proposed adjoint method in three design optimization problems that suppress unstable bifurcation: an algebraic Hopf bifurcation model, an aeroelastic model of a typical section, and a nonlinear problem based on the complex Ginzburg-Landau partial differential equation. While the current formulation addresses only a single bifurcation mode, the proposed adjoint shows great potential for efficiently handling Hopf bifurcation constraints in large scale nonlinear problems governed by partial differential equations. Its accuracy, versatility and scalability make it a promising tool for aeroelastic and aerodynamic design optimization as well as other engineering problems involving Hopf bifurcation instabilities.