Comprehensive analysis of a stochastic wireless sensor network motivated by Black-Karasinski process

Wireless sensor networks (WSNs) encounter a significant challenge in ensuring network security due to their operational constraints. This challenge stems from the potential infiltration of malware into WSNs, where a single infected node can rapidly propagate worms to neighboring nodes. To address this issue, this research introduces a stochastic S E I R S model to characterize worm spread in WSNs. Initially, we established that our model possesses a globally positive solution. Subsequently, we determine a threshold value for our stochastic system and derive a set of sufficient conditions that dictate the persistence or extinction of worm spread in WSNs based on the mean behavior. Our study reveals that environmental randomness can impede the spread of malware in WSNs. Moreover, by utilizing various parameter sets, we obtain approximate solutions that showcase these precise findings and validate the effectiveness of the proposed S E I R S model, which surpasses existing models in mitigating worm transmission in WSNs.

Trajectory tracking controller for unmanned helicopter under environmental disturbances

This paper develops a trajectory tracking control design algorithm to be applied in unmanned aerial vehicles (UAVs). The strategy is simple but effective and it is based on linear algebra theory. The proposed approach reforms the column space of a system of linear equations at each sampling time to ensure the tracking objective when environmental disturbances appear. This new formulation ensures a uniform signal without affecting the error convergence to zero (demonstration available), which is one of the main contributions of this work. A statistical method is used to tune the system control minimizing a pre-defined cost function. In addition, the convergence to zero of the tracking errors is demonstrated in this work. Finally, the controller's effectiveness is tested through several simulations in realistic test scenarios in the presence of disturbances.

Energy evaluation of low-level control in UAVs powered by lithium polymer battery

Nowadays, the energetic cost of flying in electric-powered UAVs is one of the key challenges. The continuous evolution of electrical energy storage sources is overcome by the great amount of energy required by the propulsion system. Therefore, the on-board energy is a crucial factor that needs to be further analyzed. In this work, different control strategies applied to a generic UAV propulsion system are considered and a lithium polymer battery dynamic model is included as the propulsion system energy source. Several simulations are carried out for each control strategy, and a quantitative evaluation of the influence of each control law over the actual energy consumed by the propulsion system is reported. This energy, which is delivery by the battery, is next compared against a well-known control-effort-based index. The results and analysis suggest that conclusions regarding energy savings based on control effort signals should be drawn carefully, because they do not directly represent the actual consumed energy.