1,293 research outputs found
Polynomial embedding algorithms for controllers in a behavioral framework
In this correspondence, we will establish polynomial algorithms for computation of controllers in the behavioral approach to control, in particular for the computation of controllers that regularly implement a given desired behavior and for controllers that achieve pole placement and stabilization by behavioral full interconnection and partial interconnection. These synthesis problems were studied before in articles by Belur and Trentelman, Rocha and Wood, and Willems in the reference section. In the algorithms, we will apply ideas around the unimodular and stable embedding problems. The algorithms that are presented in this correspondence can be implemented by means of the Polynomial Toolbox of Matlab
Direct data-driven state-feedback control of general nonlinear systems
Through the use of the Fundamental Lemma for linear systems, a direct
data-driven state-feedback control synthesis method is presented for a rather
general class of nonlinear (NL) systems. The core idea is to develop a
data-driven representation of the so-called velocity-form, i.e., the
time-difference dynamics, of the NL system, which is shown to admit a direct
linear parameter-varying (LPV) representation. By applying the LPV extension of
the Fundamental Lemma in this velocity domain, a state-feedback controller is
directly synthesized to provide asymptotic stability and dissipativity of the
velocity-form. By using realization theory, the synthesized controller is
realized as a NL state-feedback law for the original unknown NL system with
guarantees of universal shifted stability and dissipativity, i.e., stability
and dissipativity w.r.t. any (forced) equilibrium point, of the closed-loop
behavior. This is achieved by the use of a single sequence of data from the
system and a predefined basis function set to span the scheduling map. The
applicability of the results is demonstrated on a simulation example of an
unbalanced disc.Comment: Accepted for the 62nd IEEE Conference on Decision and Control
(CDC2023
Self-Evaluation Applied Mathematics 2003-2008 University of Twente
This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008
Embodied Evolution in Collective Robotics: A Review
This paper provides an overview of evolutionary robotics techniques applied
to on-line distributed evolution for robot collectives -- namely, embodied
evolution. It provides a definition of embodied evolution as well as a thorough
description of the underlying concepts and mechanisms. The paper also presents
a comprehensive summary of research published in the field since its inception
(1999-2017), providing various perspectives to identify the major trends. In
particular, we identify a shift from considering embodied evolution as a
parallel search method within small robot collectives (fewer than 10 robots) to
embodied evolution as an on-line distributed learning method for designing
collective behaviours in swarm-like collectives. The paper concludes with a
discussion of applications and open questions, providing a milestone for past
and an inspiration for future research.Comment: 23 pages, 1 figure, 1 tabl
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