Data- and Response-Surface-Driven Design Assistant for Controlled Flexible Multibody Systems

Prof. Dr.-Ing. habil. Hon. Prof. (NUST) Dieter Bestle (Cottbus)
Prof. Dr.-Ing. Prof. E.h. Peter Eberhard (Stuttgart)

Project goals

  • development of strategies for the joint mechanical and control design of elastic multibody systems
  • strategies enabling efficient analysis of large-scale systems for automated design
  • design objectives for elastic systems including transient phenomena and effects not covered by formalized criteria, including generalized notions of controllability
  • machine-learned surrogates, objectives and control strategies
  • robust design regarding manufacturing uncertainties and operation conditions

Preliminary work

by ITM

  • generic methods for multibody system modeling and optimization
  • modeling, model-order reduction and simulation of elastic multibody systems
  • control strategies, especially optimal control based on model predictive control

by TMF

  • sensitivity analysis and multi-objective optimization of multibody systems
  • design concepts for complex technical systems on industrial scale (turbo machinery and automotive)
  • metamodeling and AI strategies for design
00:06
00:02

First Phase Achievements

A short overview about goals achieved during the first phase

  • implementation and benchmarking of different neural networks for the dimensional synthesis of four-bar linkages
  • intuitive design assistant for the generation of task-specific four-bar linkages including desired velocity profiles
  • automatic control design based solely on data-driven methods
  • hardware demonstrator for data generation and the comparison of simulation and real-world experiments
  • simulation of mechanisms with flexible components and application of data-driven control

Interactive Design Assistant

The presented design assistant allows for an almost instantaneous design of path-specific four-bar linkages. In a first step, the user draws a target path which should be followed. A neural network is then queried on the backend and the proposed mechanism with its corresponding path are plotted. During a second step, the user can define a desired velocity profile for the automatic generation of a suitable controller. For the entire pipeline no profound mechanism knowledge is required as long as data can be collected by simulation.

Mechanism Design Assistant

01:18

Design Assistant Pipeline

02:31
00:44

Potential contribution of modules to a holistic design assistant system

  • module for control design and controller synthesis
  • module for mechanical design of dynamical technical systems
  • module to assess (generalized notions of) controllability of flexible multibody systems
  • optimization-driven assistant for joint design of mechanics and control
  • surrogate models for elastic multibody systems
  • benchmark experiment for validating control strategies

First Phase Publications

  1. Grandas Franco, J.C.; Bestle, D.; Niehoff, M. (2023). Modeling and Optimization of a Controlled Lambda Robot via Surrogate Models. In: Proc. of NAFEMS Multibody Dynamics Conference, Munich, pp. 63-66.
  2. Kayatas, Z.; Bestle, D.; Bestle, P.; Reick, R. (2023). Generation of Realistic Cut-in Maneuvers to Support Safety Assessment of Advanced Driver Assistance Systems. Applied Mechanics 4, pp. 1066-1077.
  3. Niehoff, M.; Bestle, D.; Kupijai, P. (2023). Model-based Design Optimization Taking into Account Design Viability via Classification. Proc. of NAFEMS World Congress, Tampa, USA.
  4. Bielitz, T., & Bestle, D. (2023). Identification of Dynamic Systems Assisted by an Autoregressive Recurrent Model. In: Proc. of Applied Mathematics and Mechanics (PAMM), Vol. 23, No. 2. doi.org/10.1002/pamm.202300086
  5. Röder, B.; Ebel, H.; Eberhard, P. (2023). Towards Intelligent Design Assistants for Planar Multibody Mechanisms. In: Proc. of Applied Mathematics and Mechanics (PAMM), Vol. 23, No. 3. doi: 10.1002/pamm.202300060
  6. Hajipour, S.; Bestle, D. (2024). Data-based Design of a Tracking Controller for Planar Closed-loop Mechanisms. In: Proc. of NAFEMS Nordic Conference on AI and ML in Simulation Driven Design, Lund, Sweden.
  7. Niehoff, M.; Bestle, D.; Kupijai, P. (2024). Model-based Design Optimization Taking into Account Design Viability via Classification. Engineering Modelling, Analysis and Simulation 1, pp. 1-12.
  8. Bielitz, T.; Bestle, D. (2024). Artificial Recurrent Model for Parameter Identification of Dynamic Systems. In: Proc. of Applied Mathematics and Mechanics (PAMM), Vol. 24, No. 2. doi.org/10.1002/pamm.202400015.
  9. Bestle, D.; Bielitz T. (2024): Real-Time Models for Systems with Costly or Unknown Dynamics. In: Proc. of Applied Mathematics and Mechanics (PAMM), Vol. 24, No. 2. doi.org/10.1002/pamm.202400008.
  10. Bestle, D. (2024). Optimization Processes for Automated Design of Industrial Systems. In: K. Nachbagauer and A. Held (Eds.): Optimal Design and Control of Multibody Systems, Proc. of IUTAM Symposium 2022 on Optimal Design and Control of Multibody Systems - Adjoint Methods, Alternatives, and Beyond, Hamburg, Springer, pp. 3-15.
  11. Kayatas, Z.; Bestle, D. (2024). Scenario Identification and Classification for Supporting Assessment of Advanced Driver Assistance Systems. Applied Mechanics 5, pp. 563-578.
  12. Zhai, T.; Bestle, D. (2024). Design of Two Coupled Fuzzy Controllers for a Planar Direct Internal Reforming Solid Oxide Fuel Cell. In: Proc. of Applied Mathematics and Mechanics (PAMM), Vol. 24, No. 4. doi.org/10.1002/pamm.202400077
  13. Röder, B.; Ebel, H.; Eberhard, P. (2024) Motion and Motor-Current Data of a Four-Bar Linkage. In: DaRUS - Data Repository of the University of Stuttgart. doi.org/10.18419/DARUS-4152
  14. Wohlleben, M.; Röder, B.; Ebel, H.; Muth, L.; Sextro, W.; Eberhard, P. (2024). Hybrid Modeling of Multibody Systems: Comparison of Two Discrepancy Models for Trajectory Prediction. In: Proc.of Applied Mathematics and Mechanics (PAMM), Vol. 24, No. 2.doi.org/10.1002/pamm.202400027
  15. Ebel, H.; Delden, J. van; Lüddecke, T.; Borse, A.; Gulakala, R.; Stoffel, M.; Yadav, M.; Stender, M.; Schindler, L.; Payrebrune, K. de; Raff, M.; Remy, C.D.; Röder, B.; Eberhard, P. (2024). Data Publishing in Mechanics and Dynamics: Challenges, Guidelines, and Examples from Engineering Design. URL: https://doi.org/10.48550/arXiv.2410.18358, submitted on 27.11.2024 to Data-Centric Engineering.
  16. Payrebrune, K. de; Flasskamp, K.; Ströhla, T.; Sattel, T.; Bestle, D.; Röder, B.; Eberhard, P.; Peitz, S.; Stoffel, M.; Gulakala, R.; Borse, A.; Wohlleben, M.; Sextro, W.; Raff, M.; Remy, C. D.; Yadav, M.; Stender, M.; Delden, J. van; Lüddecke, T.; Langer, S. C.; Schultz, J.; Blech, C. (2025). The Impact of AI on Engineering Design Procedures for Dynamical Systems. Technische Mechanik 45, pp. 1-23.
  17. Röder, B.; Hajipour, S.; Ebel, H.; Eberhard, P.; Bestle, D. (2025). Automated Design of a Four-bar Mechanism Starting from Hand Drawings of Desired Coupler Trajectories and Velocity Profiles. J. Mechanics Based Design of Structures and Machines,1-25.
  18. Röder, B.; Ebel, H.; Berkemeier, M.; Eberhard, P. (2024). A Dual-Network Approach for Avoiding Feature Ambiguity in the Synthesis of Crank-Driven Four-Bar Linkages. Multibody System Dynamics, 2025. DOI: 10.1007/s11044-025-10104-x
  19. Hajipour, S.; Bestle, D. ; Zhai, T. (2025). Data-Driven Sliding Mode Control of a Parallel 2D-Robot. In: Proc. of 8th International Conference on Intelligent Robotics and Control Engineering (IRCE), Kunming, China, pp. 75-80, doi: 10.1109/IRCE66030.2025.11203089.
  20. Hajipour, S.; Bestle, D. (2025). Surrogate-Based Robust Tracking Controller for a Lambda Robot. In: Proc. of Applied Mathematics and Mechanics (PAMM), no. 3: e70017, doi.org/10.1002/pamm.70017

Contact

Prof. Dr.-Ing. habil. Hon. Prof. (NUST) Dieter Bestle
Technische Universität Cottbus-Senftenberg
Siemens-Halske-Ring 14
03046 Cottbus
Tel.: +49 355 69 3023
Fax: +49 355 69 3038
Email: bestle@b-tu.de

Further Information

Prof. Dr.-Ing. Prof. E.h. Peter Eberhard
Universität Stuttgart
Pfaffenwaldring 9
70569 Stuttgart
Tel.:  +49 711 685 66388
Fax:  +49 711 685 66400
Email: peter.eberhard@itm.uni-stuttgart.de

Further Information

Sanam Hajipour Talkouei
Email: hajipour@b-tu.de

Benedict Röder
Email: benedict.roeder@itm.uni-stuttgart.de

To the top of the page