2021
DOI: 10.3390/act10110301
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Advanced Controller Development Based on eFMI with Applications to Automotive Vertical Dynamics Control

Abstract: High-level modeling languages facilitate system modeling and the development of control systems. This is mainly achieved by the automated handling of differential algebraic equations which describe the dynamics of the modeled systems across different physical domains. A wide selection of model libraries provides additional support to the modeling process. Nevertheless, deployment on embedded targets poses a challenge and usually requires manual modification and reimplementation of the control system. The novel… Show more

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Cited by 4 publications
(10 citation statements)
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“…In this setup, the EKF-SR was successfully integrated in a small-scale production series ECU and employed in a real vehicle test drive under demanding real-time conditions, and has thus demonstrated its applicability. The complete use case, also containing a control system, is described in [28] and the tool chain and the results are briefly summarized in the following subsection.…”
Section: Application On Embedded Systemsmentioning
confidence: 99%
See 1 more Smart Citation
“…In this setup, the EKF-SR was successfully integrated in a small-scale production series ECU and employed in a real vehicle test drive under demanding real-time conditions, and has thus demonstrated its applicability. The complete use case, also containing a control system, is described in [28] and the tool chain and the results are briefly summarized in the following subsection.…”
Section: Application On Embedded Systemsmentioning
confidence: 99%
“…Differences between the two scenarios relate to the underlying estimation problem, i.e., to the vehicle prediction models applied, the Kalman filter variant used, and the system on which the state estimation library is deployed. The first of these application examples is covered only briefly, since related results have already been published in another context in [28], whereas the second example is shown and discussed in more detail.…”
Section: Application On Embedded Systemsmentioning
confidence: 99%
“…Under this case, the right term of inequality (24) can be viewed as an upper bound of e T zi (k + 1)e zi (k + 1) , and "min Tr{β i (k)} + Tr{γ i (k)}" can be treated as the optimization objective to solve the local intermediate observer gain L i (k). Now, the distributed weighting matrix Ω(k) is determined by solving the convex optimization problem (14). Define e F (k)…”
Section: Distributed Fusion Estimation Based On Intermediate Variablementioning
confidence: 99%
“…. The disturbance signal and measurement noises are given by 3,4,5,6,7,8,9,10,11,12,13,14) are random variables that can be generated by the function "rand" of MATLAB. The parameter µ of the intermediate observer is 1.…”
Section: Simulation Examplesmentioning
confidence: 99%
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