Stability margins and model-free control: A first look

Fliess, Michel; Join, Cédric

doi:10.1109/ecc.2014.6862167

Cited by 46 publications

(26 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The features of the MFBM are similar to those in algebraic estimation methods [35]. In addition, the MFBM can be considered as a generalization of the algebraic estimation methods in some cases (see, e.g., [36]- [41]). The contributions of the paper are as follows:…”

Section: Introductionmentioning

confidence: 90%

Intelligent Proportional–Integral–Derivative Control-Based Modulating Functions for Laser Beam Pointing and Stabilization

Ndoye

Asiri

Aloufi

et al. 2020

IEEE Trans. Contr. Syst. Technol.

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 90%

Intelligent Proportional–Integral–Derivative Control-Based Modulating Functions for Laser Beam Pointing and Stabilization

Ndoye

Asiri

Aloufi

et al. 2020

IEEE Trans. Contr. Syst. Technol.

View full text Add to dashboard Cite

“…Thus, they may seem to be inadequate in the case of typical servo drives. However, when studying the control design based on the "flatness" theory [6,8,9], we may find that in so-called "model free", or "intelligent" PID control, such purely integral models are frequently used for an approximation of plants with constrained velocity signals in their step responses.…”

Section: Considered Plant and Filter Dynamicsmentioning

confidence: 99%

PID and filtered PID control design with application to a positional servo drive

Bélai¹,

Huba²,

Burn³

et al. 2019

Kybernetika

View full text Add to dashboard Cite

“…In this document, the variables and notations in Table I, with their meaning are used. [12], [13]). For obvious reasons let us insist here on its applications to intelligent transportation systems: see [1], [8], [41], [42], and [32].…”

Section: Or Control Purposesmentioning

confidence: 99%

An Efficient Model-Free Setting for Longitudinal and Lateral Vehicle Control: Validation Through the Interconnected Pro-SiVIC/RTMaps Prototyping Platform

Menhour

d’Andréa-Novel

Fliess

et al. 2018

IEEE Trans. Intell. Transport. Syst.

Self Cite

View full text Add to dashboard Cite

Abstract-In this paper, the problem of tracking desired longitudinal and lateral motions for a vehicle is addressed. Let us point out that a "good" modeling is often quite difficult or even impossible to obtain. It is due for example to parametric uncertainties, for the vehicle mass, inertia or for the interaction forces between the wheels and the road pavement. To overcome this type of difficulties, we consider a model-free control approach leading to "intelligent" controllers. The longitudinal and the lateral motions, on one hand, and the driving/braking torques and the steering wheel angle, on the other hand, are respectively the output and the input variables. An important part of this work is dedicated to present simulation results with actual data. Actual data, used in Matlab as reference trajectories, have been previously recorded with an instrumented Peugeot 406 experimental car. The simulation results show the efficiency of our approach. Some comparisons with a nonlinear flatnessbased control in one hand, and with a classical PID control in another hand confirm this analysis. Other virtual data have been generated through the interconnected platform SiVIC/RTMaps, which is a virtual simulation platform for prototyping and validation of advanced driving assistance systems.

show abstract

Stability margins and model-free control: A first look

Abstract: We show that the open-loop transfer functions and the stability margins may be defined within the recent model-free control setting. Several convincing computer experiments are presented including one which studies the robustness with respect to delays.

Cited by 46 publications

References 22 publications

Intelligent Proportional–Integral–Derivative Control-Based Modulating Functions for Laser Beam Pointing and Stabilization

Intelligent Proportional–Integral–Derivative Control-Based Modulating Functions for Laser Beam Pointing and Stabilization

PID and filtered PID control design with application to a positional servo drive

An Efficient Model-Free Setting for Longitudinal and Lateral Vehicle Control: Validation Through the Interconnected Pro-SiVIC/RTMaps Prototyping Platform

Contact Info

Product

Resources

About