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Engineering - Robotics | Modeling, Design, and Simulation of Systems with Uncertainties

Modeling, Design, and Simulation of Systems with Uncertainties

Rauh, Andreas, Auer, Ekaterina (Eds.)

2011, XX, 356 p.

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  • Survey of modern techniques for handling uncertainties in modeling, design and simulation of dynamic systems
  • Includes real-life application scenarios
  • Written by experts in the field

To describe the true behavior of most real-world systems with sufficient accuracy, engineers have to overcome difficulties arising from their lack of knowledge about certain parts of a process or from the impossibility of characterizing it with absolute certainty. Depending on the application at hand, uncertainties in modeling and measurements can be represented in different ways. For example, bounded uncertainties can be described by intervals, affine forms or general polynomial enclosures such as Taylor models, whereas stochastic uncertainties can be characterized in the form of a distribution described, for example, by the mean value, the standard deviation and higher-order moments.

The goal of this Special Volume on Modeling, Design, and Simulation of Systems with Uncertainties is to cover modern methods for dealing with the challenges presented by imprecise or unavailable information. All contributions tackle the topic from the point of view of control, state and parameter estimation, optimization and simulation.

Thematically, this volume can be divided into two parts. In the first we present works highlighting the theoretic background and current research on algorithmic approaches in the field of uncertainty handling, together with their reliable software implementation. The second part is concerned with real-life application scenarios from various areas including but not limited to mechatronics, robotics, and biomedical engineering.

Content Level » Research

Keywords » Aleatory uncertainties - Epistemological uncertainties - Interval methods - Verified system design

Related subjects » Applications - Robotics - Software Engineering

Table of contents 

Part 1: Theoretic Background and Software Implementation

1.      Nedialko S. Nedialkov:
Implementing a Rigorous ODE Solver through Literate Programming

2.      Sergey P. Shary:
Inner Interval Estimation of the Solution Sets to Interval Linear Systems

3.      Andreas Rauh, Harald Aschemann:
Structural Analysis for the Design of Reliable Controllers and State Estimators for Uncertain Dynamical Systems

4.      Matthias Althoff, Bruce H. Krogh, Olaf Stursberg:
Analyzing Reachability of Dynamic Systems with Parametric Uncertainties

5.      Marco Kletting, Felix Antritter:
Verified Simulation for Robustness Evaluation of Tracking Controllers

6.      Luc Jaulin:
Probabilistic Set-Membership State Estimator

7.      Michel Kieffer, Mihaly Csaba Markot, Hermann Schichl, Eric Walter:
Verified Global Optimization for Estimating the Parameters of Nonlinear Models

8.      Daria Filatova, Marek Grzywaczewski:
Optimal Control of Induction Heating: Theory and Application

9.      Serena Doria:
Coherent Upper and Lower Conditional Previsions Defined by Hausdorff Outer and Inner Measures

 

Part 2: Applications: Uncertainties in Engineering

 

10.   Marco Kletting, Michel Kieffer, Eric Walter:  Two Approaches for Guaranteed State Estimation of Nonlinear Continuous-Time Models

11.   Mehrdad Moshir:
Quantifying Spacecraft Failure in an Uncertain Environment: The Case of the Jupiter Europa Orbiter

12.   Denis Efimov, Tarek Raissi, Ali Zolghadri:
Robust State and Parameter Estimation for Nonlinear Continuous-Time Systems in a Set-Membership Context

13.   Neli Dimitrova, Mikhail Krastanov:
Nonlinear Adaptive Control of a Bioprocess Model with Unknown Kinetics

14.   Ekaterina Auer, Haider Albassam, Andres Kecskemethy, Wolfram Luther:
Verified Analysis of a Model for Stance Stabilization

15.   Vasily Saurin, Georgy Kostin, Andreas Rauh, Harald Aschemann:
Adaptive Control Strategies in Heat Transfer Problems with Parameter Uncertainties Based on a Projective Approach

16.   Harald Aschemann, Dominik Schindele, Jöran Ritzke:
State and Disturbance Estimation for Robust Control of Fast Flexible Rack Feeders

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