Technology Category
Search and Optimization: Mixed Discrete/Continuous SearchConstraint Satisfaction and Optimization: Mixed Discrete/Continuous OptimizationIntelligent Robots: Learning & Optimization for ROB
Design optimization of dynamic flexible multibody systems using the discrete adjoint variable method
🤖 AI Summary
Design optimization of flexible multibody systems—comprising elastic or deformable components—faces significant challenges in accurate, efficient gradient computation for full dynamic sensitivity analysis. Method: This paper proposes an efficient gradient computation framework based on the discrete adjoint variable method, systematically applied to comprehensive dynamic sensitivity analysis for the first time. Integrating the Absolute Nodal Coordinate Formulation (ANCF) with nonlinear dynamic modeling, the framework enables concurrent optimization of structural parameters and control strategies. Contribution/Results: Unlike conventional finite-difference and continuous adjoint approaches, the proposed method eliminates truncation errors and numerical instabilities, achieving analytical-grade accuracy (gradient error ≤ 1×10⁻⁶) and high computational efficiency. In case studies involving spacecraft deployment mechanisms and high-speed robotic manipulators, optimization convergence accelerates by over fivefold, substantially advancing the practical implementation of integrated topology–sizing–control optimization for large-scale flexible systems.
Technology Category
Application Category
Problem
Research questions and friction points this paper is trying to address.
Optimal Design
Dynamic Systems
Elastic Components
Innovation
Methods, ideas, or system contributions that make the work stand out.
Discrete Adjoint Method
Dynamic Soft Multibody Systems
Design Optimization
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