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This paper introduces the concept of functional diagnosability for nonlinear dynamical uncertain models. Set-membership functional diagnosability is based on the notion of functional signature introduced in [11] extended to the set-membership framework. The link between functional diagnosability and set-membership functional diagnosability is established. Contrary to classical definitions, the study...
This paper proposes an algorithm for trajectory planning based on the motion of Brownian particles. One of the most popular approaches in path planning is to use the artificial potential fields method which, due to its easiness in implementation, might attract the robot towards a local minimum configuration, thus preventing it from reaching the desired final destination. Although there are different...
Particle swarm optimization (PSO) can be interpreted physically as a particular discretization of a stochastic damped mass-spring system. Knowledge of this analogy has been crucial to derive the PSO continuous model and to introduce different PSO family members including the generalized PSO (GPSO) algorithm, which is the generalization of PSO for any time discretization step. In this paper, we present...
The Layered Mobility Model Architecture (LEMMA) stipulates that a mobility model can be divided into five distinct layers, which communicate unidirectionally via simple interlayer interfaces. It has been shown that this general framework can be used for the creation of empirical and theoretical models, and that any mobility model can be represented by the form specified by LEMMA. The fundamental result...
The adaptive explicit-implicit tau-leaping method with automatic tau selection is a flexible algorithm for accelerated stochastic simulation of chemically reacting systems. It combines the advantages of different simulation schemes and is particularly useful when a system changes its dynamical behavior over time in the sense that it behaves well in some time periods but possesses stiffness in other...
This work introduces a new approach to modeling object trajectories in image sequences. Trajectories performed by natural objects (e.g., people, animals) typically depend on the position of each object in the scene and can change in an unpredictable way. Despite this diversity, there is often a small number of typical motion patterns based on which it is possible to explain all the observed trajectories...
Many natural and artificial systems, for example, fish school, bird flocks, robot team, are often composed of two different classes of agents: autonomous agents and leaders. The leaders have pertinent information, such as the location of the food source, while the autonomous agents make decisions according to local interactions. Then a basic problem is: how many leaders are required in order to induce...
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