Recent Research on Automotive Control at DLR Institute of System Dynamics and Control - An Overview

Brembeck, Jonathan; Bals, Johann; Baumgartner, Daniel; Bellmann, Tobias; Bieri, Caspar; Bünte, Tilman; Mirwald, Jonas; Pfeiffer, A.; Castro, Ricardo Pinto de; Otter, Martin; Ruggaber, Julian; Schreppel, Christina; Tobolar, Jakub; Ultsch, Johannes; Winter, Christoph

doi:10.1109/med48518.2020.9183043

Cited by 3 publications

References 19 publications

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Lyapunov-based fault tolerant control allocation

Castro

Brembeck

2021

Vehicle System Dynamics

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This work addresses the design of an active fault-tolerant motion controller for overactuated road vehicles. Our concept revolves around a control allocation framework, extended with Lyapunov-based stability constraints and costs. Besides the ability to cope with actuator constraints and optimal actuator reconfiguration, the proposed Lyapunov-based control allocation (LCA) allows the graceful degradation of control performance. Theoretical analysis and simulation results demonstrate that, in comparison with classical control allocation, the proposed LCA reduces tracking errors of the motion controller in the aftermath of actuator faults. Experimental tests carried out with the ROboMObil, a robotic electric vehicle prototype with wheel-based steering and traction actuation, demonstrate the effectiveness of the LCA

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Lyapunov-based fault tolerant control allocation

Castro

Brembeck

2021

Vehicle System Dynamics

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A Collision Response Model of an Ackermann Vehicle with Combined Longitudinal and Lateral Velocity

Ghosh,

Orlando,

Chakrabarty

2023

2023 IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE)

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AI-For-Mobility—A New Research Platform for AI-Based Control Methods

et al. 2023

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AI-For-Mobility (AFM) is the new research platform to investigate and implement novel control methods based on Artificial Intelligence (AI) within the Department of Vehicle System Dynamics at the German Aerospace Center (DLR). A production hybrid vehicle serves as a base platform. Since AI-based methods are data-driven, the vehicle is equipped with manifold sensors to provide the required data. They measure the vehicle’s state holistically and perceive the surrounding environment, while high performance on-board CPUs and GPUs handle the sensor data. A full by-wire control system enables the vehicle to be used for applications in the field of automated driving. Despite all modifications, it is approved for public road use and meets the driving dynamics properties of a standard road vehicle. This makes it an attractive research and test platform, both for automotive applications and technology demonstrations in other scientific fields (e.g., robotics, aviation, etc.). This paper presents the vehicle’s design and architecture in a detailed manner and shows a promising application potential of AFM in the context of AI-based control methods.

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Recent Research on Automotive Control at DLR Institute of System Dynamics and Control - An Overview

Cited by 3 publications

References 19 publications

Lyapunov-based fault tolerant control allocation

Lyapunov-based fault tolerant control allocation

A Collision Response Model of an Ackermann Vehicle with Combined Longitudinal and Lateral Velocity

AI-For-Mobility—A New Research Platform for AI-Based Control Methods

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