This paper adds to the discussion about theoretical aspects of particle swarm stability by proposing to employ stochastic Lyapunov functions and to determine the convergence set by quantifier elimination. We present a computational procedure and show that this approach leads to reevaluation and extension of previously know stability regions for PSO using a Lyapunov approach under stagnation assumptions.

Model predictive control (MPC) is a promising approach for the lateral and longitudinal control of autonomous vehicles. However, the parameterization of the MPC with respect to high-level requirements such as passenger comfort as well as lateral and longitudinal tracking is a challenging task. Numerous tuning parameters as well as conflicting requirements need to be considered. This contribution formulates the MPC tuning task as a multi-objective optimization problem. Solving it is challenging for two reasons: First, MPC-parameterizations are evaluated on an computationally expensive simulation environment. As a result, the used optimization algorithm needs to be as sampleefficient as possible. Second, for some poor parameterizations the simulation cannot be completed and therefore useful objective function values are not available (learning with crash constraints). In this contribution, we compare the sample efficiency of multi-objective particle swarm optimization (MOPSO), a genetic algorithm (NSGA-II) and multiple versions of Bayesian optimization (BO). We extend BO, by introducing an adaptive batch size to limit the computational overhead and by a method on how to deal with crash constraints. Results show, that BO works best for a small budget, NSGA-II is best for medium budgets and for large budgets none of the evaluated optimizers is superior to random search. Both proposed BO extensions are shown to be beneficial.

We reconsider non-degenerate second order superintegrable systems in dimension two as geometric structures on conformal surfaces. This extends a formalism developed by the authors, initially introduced for (pseudo-)Riemannian manifolds of dimension three and higher. The governing equations of non-degenerate second order superintegrability in dimension two are structurally significantly different from those valid in higher dimensions. Specifically, we find conformally covariant structural equations, allowing one to classify the (conformal classes of) non-degenerate second order superintegrable systems on conformal surfaces geometrically. We then specialise to second order properly superintegrable systems on surfaces with a (pseudo-)Riemannian metric and obtain structural equations in accordance with the known equations for Euclidean space. We finally give a single explicit set of purely algebraic equations defining the variety parametrising such systems on all constant curvature surfaces.

Color symmetry implies that the colors of geometrical objects are assigned according to their symmetry properties. It is defined by associating the elements of the symmetry group with a color permutation. I use this concept for generative art and apply symmetry-consistent color distortions to images of paintings by Johannes Vermeer. The color permutations are realized as mappings of the HSV color space onto itself.

We consider an application-oriented nonlinear control of centrifugal compressors. Industrial applications require the compressor system to adjust to variable process demands and to be restricted to the valid operation range (e.g. surge limit). We modify a compressor model of Gravdahl and Egeland to account for characteristic features of industrial compressors and combine the framework of nonlinear output regulation via the internal model principle with MIN/MAX-override control in order to implement trajectory tracking between given state constraints. Furthermore the switching scheme as well as the practical stability of the closed-loop MIMO system is analysed by the corresponding switched and impulsive error system. The override control is demonstrated by applying discharge pressure control, anti-surge control and maximum discharge pressure limitation.

Coevolutionary games cast players that may change their strategies as well as their networks of interaction. In this paper a framework is introduced for describing coevolutionary game dynamics by landscape models. It is shown that coevolutionary games invoke dynamic landscapes. Numerical experiments are shown for a prisoner's dilemma (PD) and a snow drift (SD) game that both use either birth-death (BD) or death-birth (DB) strategy updating. The resulting landscapes are analyzed with respect to modality and ruggedness