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This paper introduces a new concept of partial observability for nonlinear systems. This new approach enables a quantitative analysis on the observability of an individual state variable and unknown parameters of a nonlinear dynamics even when the system is not observable in the traditional sense. The paper develops theoretical properties of partial observability and its computational algorithms. These results are applied and validated on a nonstandard estimation problem of detecting the internal cooperating strategy of a particular adversarial swarm model. Partial observability analysis on the parameters that define the cooperating strategy reveals interesting findings. For example, some parameters are observable even when the swarm is at a steady state that is not observable in traditional sense. It is also shown that observability of the internal cooperating strategy depends on both the swarm trajectory and the time window of the measurement. Motivated by these findings, a variational method of estimation based on the dynamic optimization of a cost function is proposed. Simulation results show that the proposed estimation method outperforms Kalman filters. The results in this paper provide useful tools for applications involving adversarial swarms, including defense against swarm attacks and herding of biological swarms.

One of the major issues when applying truck destination choice models with a large number of alternatives is how to sample a set of non-chosen traffic analysis zones (TAZs) to construct a destination choice set. Despite the large number of studies applying various sampling strategies, the question remains as to what are optimal strategies in model development. This study examined how the sampling strategies affect the performances of truck destination choice models. Two sampling methods (simple random sampling and stratified importance sampling) and four different sample sizes were tested using the truck trip data of Korea. For stratified importance sampling, Moran's I statistics were used to divide the entire study area into multiple strata, and Neyman allocation was used to determine the appropriate number of samples for each stratum. The truck trip productions were distributed by a Monte Carlo simulation, and two measurements of effectiveness (MOEs), average trip length (ATL) and trip length distribution (TLD), were used to evaluate and compare the performance of the destination choice models with respect to the sampling strategy. The results showed that the models using stratified importance sampling with smaller sample sizes performed better than others. Key words: destination choice model, sampling strategy, spatial autocorrelation, Moran's I, simple random sampling, stratified importance sampling, sample sizes. L'un des enjeux majeurs de l'application des modeles de choix des destinations de camions en presence d'un grand nombre de choix est de savoir comment echantillonner un ensemble de zones non selectionnees d'analyse de la circulation (TAZ) afin de construire un ensemble de choix de destinations. Malgre le grand nombre d'etudes utilisant diverses strategies d'echantillonnage, il reste a determiner la strategie optimale dans le developpement du modele. La presente etude a examine comment les strategies d'echantillonnage affectent le rendement des modeles de choix de la destination des camions. Deux methodes d'echantillonnage (l'echantillonnage aleatoire simple et l'echantillonnage par stratification) et quatre tailles differentes d'echantillons ont ete testees en utilisant les donnees de voyages de camions en Coree. Pour la methode d'echantillonnage par stratification, les statistiques I de Moran ont ete utilisees pour diviser la zone complete de l'etude en couches multiples, et la repartition de Neyman a ete utilisee pour determiner le nombre approprie d'echantillons pour chaque niveau. Les donnees sur les voyages de camions ont ete distribuees par une simulation de Monte Carlo. Deux mesures d'efficacite, la duree moyenne d'un voyage et la distribution de la duree des voyages ont ete utilisees pour evaluer et comparer la performance des modeles de choix de la destination par rapport a la strategie d'echantillonnage. Les resultats ont montre que les modeles utilisant l'echantillonnage par stratification et des echantillons plus petits produisent de meilleurs resultats que les autres. [Traduit par la Redaction] Mots-cles : modele de choix de destination, strategie d'echantillonnage, autocorrelation spatiale, I de Moran, echantillonnage aleatoire simple, echantillonnage par stratification, dimensions des echantillons., Introduction Destination choice models are based on random utility maximization where a decision maker's choice would be a reflection of the alternative with the highest preference or utility. One of [...]

For CubeSats requiring high pointing accuracy and slewing agility, ground-based hardware-in-the-loop simulations are strongly demanded to test and validate spacecraft subsystems and guidance, navigation, and control algorithms. In this article, a magnetic attitude control system (MACS) testbed for a CubeSat is developed utilizing a spherical air bearing and a Helmholtz cage. The design, development, and verification procedure of MACS is presented together with different test scenarios. To generate enough torque with the magnetorquer system in the dynamic testbed, the Helmholtz coil system of the testbed has driven to provide an augmented magnetic field. As an example of experimentation, the B-dot control algorithm was implemented to dissipate the angular momentum of the dynamic MACS testbed. The experimental results were compared with those of the numerical simulations. [ABSTRACT FROM AUTHOR]

SUMMARY: In this paper, a force and torque controller for aerial manipulation is developed using an unmanned aerial vehicle equipped with a robotic arm to interact near or on a vertical surface such as a wall. Control of aerial manipulators interacting with the environment is a challenging task due to dynamic interactions between aerial vehicles, robotic arms, and environment. To achieve this, modeling of aerial manipulators is first investigated and presented considering interaction with the environment. Nonlinear models of generic aerial manipulators, as well as of a prototype aerial manipulator composed of a hexacopter with a three-joint robotic arm, are established. An equilibrium-based force and torque controller is developed to conduct tasks that require the aerial manipulator to exert forces and torques on a wall. Simulations and experiments validate the performance of the controller that successfully applies desired forces and torques to an object fixed on a wall while flying near the wall. [ABSTRACT FROM AUTHOR]