Model-free control
Michel Fliess,Cédric Join +1 more
TL;DR: Model-free control and the corresponding ‘intelligent’ PID controllers (iPIDs), which already had many successful concrete applications, are presented here for the first time in an unified manner, where the new advances are taken into account.
read more
Abstract: ''Model-free control'' and the corresponding ''intelligent'' PID controllers (iPIDs), which already had many successful concrete applications, are presented here for the first time in an unified manner, where the new advances are taken into account. The basics of model-free control is now employing some old functional analysis and some elementary differential algebra. The estimation techniques become quite straightforward via a recent online parameter identification approach. The importance of iPIs and especially of iPs is deduced from the presence of friction. The strange industrial ubiquity of classic PID's and the great difficulty for tuning them in complex situations is deduced, via an elementary sampling, from their connections with iPIDs. Several numerical simulations are presented which include some infinite-dimensional systems. They demonstrate not only the power of our intelligent controllers but also the great simplicity for tuning them.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
On the centrality of disturbance rejection in automatic control
TL;DR: A novel, unifying concept of disturbance rejector is proposed to compliment the traditional notion of controller, leading to a Copernican moment where the model-centric design philosophy is replaced by the one that is control-centric in the following sense.
458
•Posted Content
Formulas for Data-driven Control: Stabilization, Optimality and Robustness
Claudio De Persis,Pietro Tesi +1 more
TL;DR: A parametrization of linear feedback systems is derived that paves the way to solve important control problems using data-dependent linear matrix inequalities only and is remarkable in that no explicit system's matrices identification is required.
453
Model-Free Predictive Current Control of PMSM Drives Based on Extended State Observer Using Ultralocal Model
TL;DR: An improved MFPCC based on the extended state observer of PMSM drives that does not require motor parameters and needs less tuning work and lower computational time while achieving the better performance in terms of current harmonics, tracking error, and dynamic overshoot is proposed.
438
The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles?
Philip Polack,Florent Altché,Brigitte d'Andréa-Novel,Arnaud de La Fortelle +3 more
- 11 Jun 2017
TL;DR: This paper studies the kinematic bicycle model, which is often used for trajectory planning, and compares its results to a 9 degrees of freedom model, and proposes a simple and efficient consistency criterion to validate the use of this model for planning purposes.
433
References
•Book
Real and complex analysis
Walter Rudin
- 01 Jan 1966
TL;DR: In this paper, the Riesz representation theorem is used to describe the regularity properties of Borel measures and their relation to the Radon-Nikodym theorem of continuous functions.
From PID to Active Disturbance Rejection Control
TL;DR: Active disturbance rejection control is proposed, which is motivated by the ever increasing demands from industry that requires the control technology to move beyond PID, and may very well break the hold of classical PID and enter a new era of innovations.
5.9K
Flatness and defect of non-linear systems: introductory theory and examples
TL;DR: In this paper, the authors introduce flat systems, which are equivalent to linear ones via a special type of feedback called endogenous feedback, which subsumes the physical properties of a linearizing output and provides another nonlinear extension of Kalman's controllability.
Nonlinear Control Systems
Nahum Shimkin
- 01 Jan 2008
TL;DR: Feedback control theory is concerned with the analysis and design of nonlinear control systems where nonlinearity plays a significant role, either in the controlled process (plant) or in the controller itself.