Special Issue "Algorithms for Reliable Estimation, Identification and Control"

A special issue of Algorithms (ISSN 1999-4893).

Deadline for manuscript submissions: closed (31 January 2020).

Special Issue Editor

Dr. Andreas Rauh
E-Mail Website
Guest Editor
Chair of Mechatronics, Faculty of Mechanical Engineering and Marine Technology, University of Rostock, Justus-von-Liebig-Weg 6, 18059 Rostock, Germany
Interests: interval analysis; state estimation; stochastic filtering techniques; robust control; optimization

Special Issue Information

Dear Colleagues,

The optimization of feedforward and feedback controllers with respect to predefined performance criteria as well as the enhancement and verification of their robustness with respect to external disturbances and uncertain parameters are widespread aspects of current research activities. The same holds for the reliable estimation of non-measurable system states and for the identification of parameters based on uncertain measurements. Possible applications of related optimization algorithms can be found not only in the frame of a control and estimator synthesis, but also in the field of reliable modeling and in the model-based analysis of measured data.
This Special Issue aims at providing a platform for the publication of novel algorithms in the frame of reliable and optimal estimation and control. Moreover, application-oriented aspects highlighting the practical applicability of theoretical approaches are highly welcome.

Possible topics of interest include:

  • Optimal and robust control of finite-dimensional systems;
  • Optimization and robustness analysis for partial differential equations;
  • Representation of epistemic and aleatory uncertainty by means of:
  • Interval analysis; and
  • Stochastic modeling procedures;
  • Structural optimization of controllers and state observers;
  • Parameter optimization and identification;
  • Stability analysis.

Dr. Andreas Rauh
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

Open AccessArticle
Unstructured Uncertainty Based Modeling and Robust Stability Analysis of Textile-Reinforced Composites with Embedded Shape Memory Alloys
Algorithms 2020, 13(1), 24; https://doi.org/10.3390/a13010024 - 15 Jan 2020
Abstract
This paper develops the mathematical modeling and deflection control of a textile-reinforced composite integrated with shape memory actuators. The mathematical model of the system is derived using the identification method and an unstructured uncertainty approach. Based on this model and a robust stability [...] Read more.
This paper develops the mathematical modeling and deflection control of a textile-reinforced composite integrated with shape memory actuators. The mathematical model of the system is derived using the identification method and an unstructured uncertainty approach. Based on this model and a robust stability analysis, a robust proportional–integral controller is designed for controlling the deflection of the composite. We showed that the robust controller depends significantly on the modeling of the uncertainty. The performance of the proposed controller is compared with a classical one through experimental analysis. Experimental results show that the proposed controller has a better performance as it reduces the overshoot and provide robustness to uncertainty. Due to the robust design, the controller also has a wide operating range, which is advantageous for practical applications. Full article
(This article belongs to the Special Issue Algorithms for Reliable Estimation, Identification and Control)
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Open AccessArticle
Using Interval Analysis to Compute the Invariant Set of a Nonlinear Closed-Loop Control System
Algorithms 2019, 12(12), 262; https://doi.org/10.3390/a12120262 - 06 Dec 2019
Abstract
In recent years, many applications, as well as theoretical properties of interval analysis have been investigated. Without any claim for completeness, such applications and methodologies range from enclosing the effect of round-off errors in highly accurate numerical computations over simulating guaranteed enclosures of [...] Read more.
In recent years, many applications, as well as theoretical properties of interval analysis have been investigated. Without any claim for completeness, such applications and methodologies range from enclosing the effect of round-off errors in highly accurate numerical computations over simulating guaranteed enclosures of all reachable states of a dynamic system model with bounded uncertainty in parameters and initial conditions, to the solution of global optimization tasks. By exploiting the fundamental enclosure properties of interval analysis, this paper aims at computing invariant sets of nonlinear closed-loop control systems. For that purpose, Lyapunov-like functions and interval analysis are combined in a novel manner. To demonstrate the proposed techniques for enclosing invariant sets, the systems examined in this paper are controlled via sliding mode techniques with subsequently enclosing the invariant sets by an interval based set inversion technique. The applied methods for the control synthesis make use of a suitably chosen Gröbner basis, which is employed to solve Bézout’s identity. Illustrating simulation results conclude this paper to visualize the novel combination of sliding mode control with an interval based computation of invariant sets. Full article
(This article belongs to the Special Issue Algorithms for Reliable Estimation, Identification and Control)
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