arXiv subjects
Publications and source records attributed to Oleg Borisov.
The study addresses the problem of quadcopter motion control using output feedback. By applying a geometric approach, the quadcopter model is transformed into a normal form with a time-varying gain coefficient, which is subsequently made stationary through double integration of the control input. A robust output feedback control law is synthesised based on the extended observer method.
A complete model of quadcopter motion for the task of dynamic positioning at a specified point is derived. Based on this model, two control algorithms are proposed. The first one generalizes previously obtained results to the case of a varying yaw angle. The second control algorithm addresses the above problem using a simplified regulator tuning methodology.
A complete model of the motion of a quadcopter along a smooth spatial trajectory is presented. Based on the model, a robust algorithm is proposed for controlling a quadcopter using measurements of linear coordinates and yaw angle. By introducing additional integrators, a dynamic control algorithm with a simplified controller tuning methodology is obtained. The control law is synthesized within the geometric approach, and its stability is proven. A realizable output-feedback version using an extended observer is also given. The results enable coordinated trajectory following in three-dimensional space despite unmeasured disturbances and incomplete state information.
Recent research has shown that mixed-initiative conversational search, based on the interaction between users and computers to clarify and improve a query, provides enormous advantages. Nonetheless, incorporating additional information provided by the user from the conversation poses some challenges. In fact, further interactions could confuse the system as a user might use words irrelevant to the information need but crucial for correct sentence construction in the context of multi-turn conversations. To this aim, in this paper, we have collected two conversational keyword extraction datasets and propose an end-to-end document retrieval pipeline incorporating them. Furthermore, we study the performance of two neural keyword extraction models, namely, BERT and sequence to sequence, in terms of extraction accuracy and human annotation. Finally, we study the effect of keyword extraction on the end-to-end neural IR performance and show that our approach beats state-of-the-art IR models. We make the two datasets publicly available to foster research in this area.
We propose the quantitative mean-field theory of mechanical unfolding of a globule formed by long flexible homopolymer chain collapsed in poor solvent and subjected to extensional deformation. We demonstrate that depending on the degree of polymerization and solvent quality (quantified by the Flory-Huggins $χ$ parameter) the mechanical unfolding of the collapsed chain may either occur continuously (by passing a sequence of uniformly elongated configurations) or involves intra-molecular micro-phase coexistence of a collapsed and a stretched segment followed by an abrupt unraveling transition. The force-extension curves are obtained and quantitatively compared to our recent results of numerical self-consistent field (SCF) simulations. The phase diagrams for extended homopolymer chains in poor solvent comprising one- and two-phase regions are calculated for different chain length or/and solvent quality.