1,166 research outputs found

    Evolutionary multi-objective optimisation with preferences for multivariable PI controller tuning

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    Multi-objective optimisation design procedures have shown to be a valuable tool for control engineers. They enable the designer having a close embedment of the tuning process for a wide variety of applica- tions. In such procedures, evolutionary multi-objective optimisation has been extensively used for PI and PID controller tuning; one reason for this is due to their flexibility to include mechanisms in order to en- hance convergence and diversity. Although its usability, when dealing with multi-variable processes, the resulting Pareto front approximation might not be useful, due to the number of design objectives stated. That is, a vast region of the objective space might be impractical or useless a priori, due to the strong degradation in some of the design objectives. In this paper preference handling techniques are incorpo- rated into the optimisation process, seeking to improve the pertinency of the approximated Pareto front for multi-variable PI controller tuning. That is, the inclusion of preferences into the optimisation process, in order to seek actively for a pertinent Pareto front approximation. With such approach, it is possible to tune a multi-variable PI controller, fulfilling several design objectives, using previous knowledge from the designer on the expected trade-off performance. This is validated with a well-known benchmark exam- ple in multi-variable control. Control tests show the usefulness of the proposed approach when compared with other tuning techniques.This work was partially supported by the fellowship BJT-304804/2014-2 from the National Council of Scientific and Technologic Development of Brazil (CNPq) and by EVO-CONTROL project (ref. PROMETEO/2012/028, Generalitat Valenciana - Spain).Reynoso Meza, G.; SanchĂ­s Saez, J.; Blasco, X.; Freire, RZ. (2016). Evolutionary multi-objective optimisation with preferences for multivariable PI controller tuning. Expert Systems with Applications. 51:120-133. doi:10.1016/j.eswa.2015.11.028S1201335

    Massive MIMO-based Localization and Mapping Exploiting Phase Information of Multipath Components

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    In this paper, we present a robust multipath-based localization and mapping framework that exploits the phases of specular multipath components (MPCs) using a massive multiple-input multiple-output (MIMO) array at the base station. Utilizing the phase information related to the propagation distances of the MPCs enables the possibility of localization with extraordinary accuracy even with limited bandwidth. The specular MPC parameters along with the parameters of the noise and the dense multipath component (DMC) are tracked using an extended Kalman filter (EKF), which enables to preserve the distance-related phase changes of the MPC complex amplitudes. The DMC comprises all non-resolvable MPCs, which occur due to finite measurement aperture. The estimation of the DMC parameters enhances the estimation quality of the specular MPCs and therefore also the quality of localization and mapping. The estimated MPC propagation distances are subsequently used as input to a distance-based localization and mapping algorithm. This algorithm does not need prior knowledge about the surrounding environment and base station position. The performance is demonstrated with real radio-channel measurements using an antenna array with 128 ports at the base station side and a standard cellular signal bandwidth of 40 MHz. The results show that high accuracy localization is possible even with such a low bandwidth.Comment: 14 pages (two columns), 13 figures. This work has been submitted to the IEEE Transaction on Wireless Communications for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

    The Impact of Channel Feedback on Opportunistic Relay Selection for Hybrid-ARQ in Wireless Networks

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    This paper presents a decentralized relay selection protocol for a dense wireless network and describes channel feedback strategies that improve its performance. The proposed selection protocol supports hybrid automatic-repeat-request transmission where relays forward parity information to the destination in the event of a decoding error. Channel feedback is employed for refining the relay selection process and for selecting an appropriate transmission mode in a proposed adaptive modulation transmission framework. An approximation of the throughput of the proposed adaptive modulation strategy is presented, and the dependence of the throughput on system parameters such as the relay contention probability and the adaptive modulation switching point is illustrated via maximization of this approximation. Simulations show that the throughput of the proposed selection strategy is comparable to that yielded by a centralized selection approach that relies on geographic information.Comment: 30 pages, 9 figures, submitted to the IEEE Transactions on Vehicular Technology, revised March 200

    Teaching electronics-ICT : from focus and structure to practical realizations

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    We present a four-year electronics-ICT educational master program at Ghent University in Belgium. The students develop knowledge and skills from novice to experienced electronic circuit designers. In the corresponding topics, the immersion into engineering problems is deepened. The horizontal and vertical alignment of courses in the four-year master program at our university is discussed. The curriculum of the four-year master program is highly projectoriented and all topics are clustered around a well-considered set of standards. This clustering supports the logical structure of the program, with students gradually acquiring the necessary competences. All standards and their mutual interaction are extensively discussed in the paper. We also focus on four design-implement projects included in the electronics-ICT program, explicitly following CDIO-guidelines. Whereas the first-year project has a limited level of difficulty, the challenges increase significantly in the course of the next years. Students learn that product design is an iterative process on different levels, where the design strategy can be changed continuously based on important and crucial feedback. Different evaluations have demonstrated that our students are not only aware of CDIO-principles, but are also convinced of the quality of the results obtained by following the standards
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