Andreas Rauh

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In this paper, an overview of the potential use of validated techniques for the analysis and design of controllers for linear and nonlinear dynamical systems with uncertainties is given. In addition to robust pole assignment for linear dynamical systems with parameter uncertainties, mathematical system models and computational techniques are considered in(More)
This paper is concerned with recursively estimating the internal state of a nonlinear dynamic system by processing noisy measurements and the known system input. In the case of continuous states, an exact analytic representation of the probability density characterizing the estimate is generally too complex for recursive estimation or even impossible to(More)
In this paper, interval simulation methods are presented to determine guaranteed enclosures of state variables of an activated sludge process in biological wastewater treatment. This process is characterized by nonlinearities and uncertain but bounded parameters. In uncertain systems an axis-parallel interval box is mapped to a complexly shaped region in(More)
The theoretical background and the implementation of a new interval arithmetic approach for solving sets of differential-algebraic equations (DAEs) are presented. The proposed approach computes guaranteed enclosures of all reachable states of dynamical systems described by sets of DAEs with uncertainties in both initial conditions and system parameters. The(More)
In many control applications, we are interested in accurate trajectory tracking. This is especially true for cases in which exact analytic solutions are not available because initial states are not consistent with the desired state or output trajectories or because parameters are significantly uncertain. In these cases, control strategies can be derived on(More)
Control strategies for nonlinear dynamical systems often make use of special system properties, which are, for example, differential flatness or exact input-output as well as input-to-state linearizability. However, approaches using these properties are unavoidably limited to specific classes of mathematical models. To generalize design procedures and to(More)
ValEncIA-IVP is a verified solver for initial value problems for sets of ordinary differential equations which determines guaranteed enclosures of all reachable states. In this paper, we present its new features which allow for a wider application domain. They also improve the performance of ValEncIA-IVP. Especially for the simulation of asymptotically(More)