Adjoint sensitivity analysis method for dynamic optimization of multibody systems considering collision and friction

被引:1
|
作者
Zhang, Mengru [1 ]
Song, Ningning [1 ]
Wang, Hao [1 ]
Peng, Haijun [1 ]
机构
[1] Dalian Univ Technol, Dept Engn Mech, State Key Lab Struct Anal Ind Equipment, Dalian 116024, Peoples R China
基金
中国国家自然科学基金;
关键词
Multibody system; Contact and friction; Dynamic optimization; Sensitivity analysis; Adjoint variable method; CONSTRAINTS; CONTACT; DESIGN;
D O I
10.1007/s00158-022-03334-6
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Collision and friction will cause the nonsmooth phenomenon of the state variables of mechanisms, and affect the stability and dynamic behavior of multibody systems. For the dynamic optimization of multibody systems, the optimization methods roughly include gradient-free methods and gradient methods. The gradient-free optimization methods need a lot of function evaluation, and the convergence speed is often quite slow. However, gradient optimization methods can obtain optimization results with less iterations. Among them, gradient, that is, dynamic sensitivity analysis, is inevitable and difficult, and there are few research reports. Taking contact and friction phenomena into consideration, an adjoint sensitivity analysis method for dynamic optimization of multibody systems is proposed in this paper. The calculation formulas of analytical and semi-analytical sensitivity analysis methods and optimization flow are given. In addition, the availability and engineering practicability of the proposed method are verified by the dynamic optimization examples of rigid five-bar mechanism and rigid-flexible tensegrity structure.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Adjoint sensitivity analysis method for dynamic optimization of multibody systems considering collision and friction
    Mengru Zhang
    Ningning Song
    Hao Wang
    Haijun Peng
    Structural and Multidisciplinary Optimization, 2022, 65
  • [2] Discrete Adjoint Method for the Sensitivity Analysis of Flexible Multibody Systems
    Callejo, Alfonso
    Sonneville, Valentin
    Bauchau, Olivier A.
    JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS, 2019, 14 (02):
  • [3] Dynamic Response Optimization of Complex Multibody Systems in a Penalty Formulation Using Adjoint Sensitivity
    Zhu, Yitao
    Dopico, Daniel
    Sandu, Corina
    Sandu, Adrian
    JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS, 2015, 10 (03):
  • [4] Adjoint sensitivity analysis of hybrid multibody dynamical systems
    Sebastien Corner
    Adrian Sandu
    Corina Sandu
    Multibody System Dynamics, 2020, 49 : 395 - 420
  • [5] Adjoint sensitivity analysis of hybrid multibody dynamical systems
    Corner, Sebastien
    Sandu, Corina
    Sandu, Adrian
    MULTIBODY SYSTEM DYNAMICS, 2020, 49 (04) : 395 - 420
  • [6] Design optimization of dynamic flexible multibody systems using the discrete adjoint variable method
    Ebrahimi, Mehran
    Butscher, Adrian
    Cheong, Hyunmin
    Iorio, Francesco
    COMPUTERS & STRUCTURES, 2019, 213 : 82 - 99
  • [7] SENSITIVITY ANALYSIS OF FLEXIBLE MULTIBODY SYSTEMS BASED ON THE MOTION FORMALISM AND THE DISCRETE ADJOINT METHOD
    Callejo, Alfonso
    Sonneville, Valentin
    Bauchau, Olivier A.
    PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, 2018, VOL 6, 2018,
  • [8] Inverse dynamic analysis of constrained multibody systems considering friction forces acting on kinematic joints
    Park, JH
    Yoo, HH
    Hwang, YH
    Bae, DS
    JSME INTERNATIONAL JOURNAL SERIES C-MECHANICAL SYSTEMS MACHINE ELEMENTS AND MANUFACTURING, 2000, 43 (03): : 553 - 559
  • [9] Adjoint sensitivity analysis and optimization of hysteretic dynamic systems with nonlinear viscous dampers
    Nicolò Pollini
    Oren Lavan
    Oded Amir
    Structural and Multidisciplinary Optimization, 2018, 57 : 2273 - 2289
  • [10] Adjoint sensitivity analysis and optimization of hysteretic dynamic systems with nonlinear viscous dampers
    Pollini, Nicolo
    Lavan, Oren
    Amir, Oded
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2018, 57 (06) : 2273 - 2289