201 research outputs found

    Letter to the editor

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    AbstractThis letter shows how the main result contained in a paper recently appeared in the Journal of Multivariate Analysis was in fact a particular case of a more general theorem published three years before

    Multirate control with incomplete information over Profibus-DP network

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    This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Systems Science on 2014, available online:http://www.tandfonline.com/10.1080/00207721.2013.844286When a process ¿eld bus-decentralized peripherals (Pro¿bus-DP) network is used in an industrial environment, a deterministic behaviour is usually claimed. However, due to some concerns such as bandwidth limitations, lack of synchronisation among different clocks and existence of time-varying delays, a more complex problem must be faced. This problem implies the transmission of irregular and, even, random sequences of incomplete information. The main consequence of this issue is the appearance of different sampling periods at different network devices. In this paper, this aspect is checked by means of a detailed Pro¿bus-DP timescale study. In addition, in order to deal with the different periods, a delay-dependent dual-rate proportional-integral-derivative control is introduced. Stability for the proposed control system is analysed in terms of linear matrix inequalitiesThe authors are grateful to the financial support of the Spanish Ministry of Economy and Competitivity [Research Grant TEC2012-31506].Salt Llobregat, JJ.; Casanova Calvo, V.; Cuenca Lacruz, ÁM.; Pizá Fernández, R. (2014). Multirate control with incomplete information over Profibus-DP network. International Journal of Systems Science. 45(7):1589-1605. https://doi.org/10.1080/00207721.2013.844286S15891605457Alves, M., & Tovar, E. (2007). Real-time communications over wired/wireless PROFIBUS networks supporting inter-cell mobility. Computer Networks, 51(11), 2994-3012. doi:10.1016/j.comnet.2007.01.001Boyd, S., El Ghaoui, L., Feron, E., & Balakrishnan, V. (1994). Linear Matrix Inequalities in System and Control Theory. doi:10.1137/1.9781611970777Bucher, R., & Balemi, S. (2006). Rapid controller prototyping with Matlab/Simulink and Linux. Control Engineering Practice, 14(2), 185-192. doi:10.1016/j.conengprac.2004.09.009Casanova, V., & Salt, J. (2003). Multirate control implementation for an integrated communication and control system. Control Engineering Practice, 11(11), 1335-1348. doi:10.1016/s0967-0661(02)00256-3Lee, J., Jung, W., Kang, I., Kim, Y., & Lee, G. (2004). Design of filter to reject motion artifact of pulse oximetry. Computer Standards & Interfaces, 26(3), 241-249. doi:10.1016/s0920-5489(03)00077-1Cuenca, Á., Pizá, R., Salt, J., & Sala, A. (2012). Linear Matrix Inequalities in Multirate Control over Networks. Mathematical Problems in Engineering, 2012, 1-22. doi:10.1155/2012/768212Cuenca, A., & Salt, J. (2012). RST controller design for a non-uniform multi-rate control system. Journal of Process Control, 22(10), 1865-1877. doi:10.1016/j.jprocont.2012.09.010Cuenca, Á., Salt, J., & Albertos, P. (2006). Implementation of algebraic controllers for non-conventional sampled-data systems. Real-Time Systems, 35(1), 59-89. doi:10.1007/s11241-006-9001-2Halevi, Y., & Ray, A. (1988). Integrated Communication and Control Systems: Part I—Analysis. Journal of Dynamic Systems, Measurement, and Control, 110(4), 367-373. doi:10.1115/1.3152698Khargonekar, P., Poolla, K., & Tannenbaum, A. (1985). Robust control of linear time-invariant plants using periodic compensation. IEEE Transactions on Automatic Control, 30(11), 1088-1096. doi:10.1109/tac.1985.1103841Lall, S., & Dullerud, G. (2001). An LMI solution to the robust synthesis problem for multi-rate sampled-data systems. Automatica, 37(12), 1909-1922. doi:10.1016/s0005-1098(01)00167-4Lee, I. W. C., & Dash, P. K. (2003). S-transform-based intelligent system for classification of power quality disturbance signals. IEEE Transactions on Industrial Electronics, 50(4), 800-805. doi:10.1109/tie.2003.814991Lee, C. K., Ron Hui, S. Y., & Henry Shu-Hung Chung. (2002). A 31-level cascade inverter for power applications. IEEE Transactions on Industrial Electronics, 49(3), 613-617. doi:10.1109/tie.2002.1005388Performance evaluation of control networks: Ethernet, ControlNet, and DeviceNet. (2001). IEEE Control Systems, 21(1), 66-83. doi:10.1109/37.898793Feng-Li Lian, Moyne, J., & Tilbury, D. (2002). Network design consideration for distributed control systems. IEEE Transactions on Control Systems Technology, 10(2), 297-307. doi:10.1109/87.987076Lin, J., Fei, S., & Gao, Z. (2013). Control discrete-time switched singular systems with state delays under asynchronous switching. International Journal of Systems Science, 44(6), 1089-1101. doi:10.1080/00207721.2011.652230Liou, L.-W., & Ray, A. (1991). A Stochastic Regulator for Integrated Communication and Control Systems: Part I—Formulation of Control Law. Journal of Dynamic Systems, Measurement, and Control, 113(4), 604-611. doi:10.1115/1.2896464Lorand, C., & Bauer, P. H. (2006). On Synchronization Errors in Networked Feedback Systems. IEEE Transactions on Circuits and Systems I: Regular Papers, 53(10), 2306-2317. doi:10.1109/tcsi.2006.882824Moayedi, M., Foo, Y. K., & Soh, Y. C. (2011). Filtering for networked control systems with single/multiple measurement packets subject to multiple-step measurement delays and multiple packet dropouts. International Journal of Systems Science, 42(3), 335-348. doi:10.1080/00207720903513335Peñarrocha, I., Sanchis, R., & Romero, J. A. (2012). State estimator for multisensor systems with irregular sampling and time-varying delays. International Journal of Systems Science, 43(8), 1441-1453. doi:10.1080/00207721.2011.625482Piza, R., Salt, J., Sala, A., & Cuenca, A. (2014). Hierarchical Triple-Maglev Dual-Rate Control Over a Profibus-DP Network. IEEE Transactions on Control Systems Technology, 22(1), 1-12. doi:10.1109/tcst.2012.2222883Ray, A. (1989). Introduction to networking for integrated control systems. IEEE Control Systems Magazine, 9(1), 76-79. doi:10.1109/37.16755Ray, A., & Halevi, Y. (1988). Integrated Communication and Control Systems: Part II—Design Considerations. Journal of Dynamic Systems, Measurement, and Control, 110(4), 374-381. doi:10.1115/1.3152699Sala, A., Cuenca, Á., & Salt, J. (2009). A retunable PID multi-rate controller for a networked control system. Information Sciences, 179(14), 2390-2402. doi:10.1016/j.ins.2009.02.017Salt, J., & Albertos, P. (2005). Model-based multirate controllers design. IEEE Transactions on Control Systems Technology, 13(6), 988-997. doi:10.1109/tcst.2005.857410Salt, J., Sala, A., & Albertos, P. (2011). A Transfer-Function Approach to Dual-Rate Controller Design for Unstable and Non-Minimum-Phase Plants. IEEE Transactions on Control Systems Technology, 19(5), 1186-1194. doi:10.1109/tcst.2010.2076386Schickhuber, G., & McCarthy, O. (1997). Distributed Fieldbus and control network systems. Computing & Control Engineering Journal, 8(1), 21-32. doi:10.1049/cce:19970106Sturm, J. F. (1999). Using SeDuMi 1.02, A Matlab toolbox for optimization over symmetric cones. Optimization Methods and Software, 11(1-4), 625-653. doi:10.1080/10556789908805766Tipsuwan, Y., & Chow, M.-Y. (2003). Control methodologies in networked control systems. Control Engineering Practice, 11(10), 1099-1111. doi:10.1016/s0967-0661(03)00036-4Xie, L. B., Ozkul, S., Sawant, M., Shieh, L. S., Tsai, J. S. H., & Tsai, C. H. (2013). Multi-rate digital redesign of cascaded and dynamic output feedback systems. International Journal of Systems Science, 45(8), 1757-1768. doi:10.1080/00207721.2012.752546Yang, T. C. (2006). Networked control system: a brief survey. IEE Proceedings - Control Theory and Applications, 153(4), 403-412. doi:10.1049/ip-cta:2005017

    The Architecture of the Neural System for Control of a Mobile Robot

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    Building autonomous mobile robots has been a primary aim of robotics and artificial intelligence. Artificial neural networks are capable of performing the different aspecis of autonomous drmng, such as collision-free motions, avoiding obstacles, mapping and planning of path. This paper describes the global architecture of the neural system for autonomous control of a mobile robot. Such neural system has the ability for self-training and self-organizing. The purpose of this paper is to present the key ideas and approaches underlying our research in this area

    Detecting the direction of a signal on high-dimensional spheres: Non-null and Le Cam optimality results

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    We consider one of the most important problems in directional statistics, namely the problem of testing the null hypothesis that the spike direction θ\theta of a Fisher-von Mises-Langevin distribution on the pp-dimensional unit hypersphere is equal to a given direction θ0\theta_0. After a reduction through invariance arguments, we derive local asymptotic normality (LAN) results in a general high-dimensional framework where the dimension pnp_n goes to infinity at an arbitrary rate with the sample size nn, and where the concentration κn\kappa_n behaves in a completely free way with nn, which offers a spectrum of problems ranging from arbitrarily easy to arbitrarily challenging ones. We identify various asymptotic regimes, depending on the convergence/divergence properties of (κn)(\kappa_n), that yield different contiguity rates and different limiting experiments. In each regime, we derive Le Cam optimal tests under specified κn\kappa_n and we compute, from the Le Cam third lemma, asymptotic powers of the classical Watson test under contiguous alternatives. We further establish LAN results with respect to both spike direction and concentration, which allows us to discuss optimality also under unspecified κn\kappa_n. To investigate the non-null behavior of the Watson test outside the parametric framework above, we derive its local asymptotic powers through martingale CLTs in the broader, semiparametric, model of rotationally symmetric distributions. A Monte Carlo study shows that the finite-sample behaviors of the various tests remarkably agree with our asymptotic results.Comment: 47 pages, 4 figure

    Exploring the socio-ecological factors behind the (in)active lifestyles of Spanish post-bariatric surgery patients

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    Purpose: Physical activity (PA) is considered essential for the treatment of morbid obesity and the optimization of bariatric surgery outcomes. The objective of this article was to identify the facilitators and barriers that bariatric patients perceived to do PA one year after finishing a PA programme for the promotion of a long-term active lifestyle. This objective was addressed from a socio-ecological and qualitative perspective. Methods: Nine patients (eight women and one man), aged between 31 and 59 years, participated in semi-structured interviews directly following the PA programme and one year after it. A content analysis was carried out to analyze the qualitative data. Results: Weight loss, improvement of physical fitness, perceived competence, and enjoyment were the main facilitators of PA. Complexes related to skin folds, osteoarthritis, perceived unfavourable weather conditions, lack of social support and economic resources, long workdays, lack of specific PA programmes, and other passive leisure preferences were the main barriers to participate in PA. Conclusions: Results highlight the important interplay between personal, social environmental, and physical environmental factors to explain (in)active behaviours of bariatric patients. The findings of this article could be useful for future research and interventions aimed at promoting PA in bariatric patients

    Bryophytes of Europe Traits (BET) dataset: a fundamental tool for ecological studies

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    Bryophytes are a diverse group of organisms with unique properties, yet they are severely underrepresented in plant trait databases. Building on the recently published European Red List of bryophytes and previous trait compilations, we present the Bryophytes of Europe Traits (BET) data set, including biological traits such as those related to life history, growth habit, sexual and vegetative reproduction; ecological traits such as indicator values, substrate and habitat; and bioclimatic variables based on the species' European range. The data set includes values for 65 traits and 25 bio-climatic variables, containing more than 135,000 trait values with a completeness of 82.7% on average. The data set will enable future studies in bryophyte biology, ecology and conservation, and may help to answer fundamental questions in bryology.info:eu-repo/semantics/publishedVersio

    Rejection of mismatched disturbances for systems with input delay via a predictive extended state observer

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    [EN] The problem of output stabilization and disturbance rejection for input-delayed systems is tackled in this work. First, a suitable transformation is introduced to translate mismatched disturbances into an equivalent input disturbance. Then, an extended state observer is combined with a predictive observer structure to obtain a future estimation of both the state and the disturbance. A disturbance model is assumed to be known but attenuation of unmodeled components is also considered. The stabilization is proved via Lyapunov-Krasovskii functionals, leading to sufficient conditions in terms of linear matrix inequalities for the closed-loop analysis and parameter tuning. The proposed strategy is illustrated through a numerical example.PROMETEOII/2013/004; Conselleria d'Educacio; Generalitat Valenciana, Grant/Award Number: TIN2014-56158-C4-4-P-AR; Ministerio de Economia y Competitividad, Grant/Award Number: FPI-UPV 2014; Universitat Politecnica de ValenciaSanz Diaz, R.; García Gil, PJ.; Fridman, E.; Albertos Pérez, P. (2018). Rejection of mismatched disturbances for systems with input delay via a predictive extended state observer. International Journal of Robust and Nonlinear Control. 28(6):2457-2467. https://doi.org/10.1002/rnc.4027S24572467286Stability and Stabilization of Systems with Time Delay. (2011). IEEE Control Systems, 31(1), 38-65. doi:10.1109/mcs.2010.939135Fridman, E. (2014). Introduction to Time-Delay Systems. Systems & Control: Foundations & Applications. doi:10.1007/978-3-319-09393-2Watanabe, K., & Ito, M. (1981). A process-model control for linear systems with delay. IEEE Transactions on Automatic Control, 26(6), 1261-1269. doi:10.1109/tac.1981.1102802Astrom, K. J., Hang, C. C., & Lim, B. C. (1994). A new Smith predictor for controlling a process with an integrator and long dead-time. IEEE Transactions on Automatic Control, 39(2), 343-345. doi:10.1109/9.272329Matausek, M. R., & Micic, A. D. (1996). A modified Smith predictor for controlling a process with an integrator and long dead-time. IEEE Transactions on Automatic Control, 41(8), 1199-1203. doi:10.1109/9.533684García, P., & Albertos, P. (2008). A new dead-time compensator to control stable and integrating processes with long dead-time. Automatica, 44(4), 1062-1071. doi:10.1016/j.automatica.2007.08.022Normey-Rico, J. E., & Camacho, E. F. (2009). Unified approach for robust dead-time compensator design. Journal of Process Control, 19(1), 38-47. doi:10.1016/j.jprocont.2008.02.003Manitius, A., & Olbrot, A. (1979). Finite spectrum assignment problem for systems with delays. IEEE Transactions on Automatic Control, 24(4), 541-552. doi:10.1109/tac.1979.1102124Artstein, Z. (1982). Linear systems with delayed controls: A reduction. IEEE Transactions on Automatic Control, 27(4), 869-879. doi:10.1109/tac.1982.1103023Krstic, M. (2008). Lyapunov tools for predictor feedbacks for delay systems: Inverse optimality and robustness to delay mismatch. Automatica, 44(11), 2930-2935. doi:10.1016/j.automatica.2008.04.010Léchappé, V., Moulay, E., Plestan, F., Glumineau, A., & Chriette, A. (2015). New predictive scheme for the control of LTI systems with input delay and unknown disturbances. Automatica, 52, 179-184. doi:10.1016/j.automatica.2014.11.003Sanz, R., Garcia, P., & Albertos, P. (2016). Enhanced disturbance rejection for a predictor-based control of LTI systems with input delay. Automatica, 72, 205-208. doi:10.1016/j.automatica.2016.05.019Basturk, H. I., & Krstic, M. (2015). Adaptive sinusoidal disturbance cancellation for unknown LTI systems despite input delay. Automatica, 58, 131-138. doi:10.1016/j.automatica.2015.05.013Basturk, H. I. (2017). Cancellation of unmatched biased sinusoidal disturbances for unknown LTI systems in the presence of state delay. Automatica, 76, 169-176. doi:10.1016/j.automatica.2016.10.006Sanz, R., Garcia, P., Albertos, P., & Zhong, Q.-C. (2016). Robust controller design for input-delayed systems using predictive feedback and an uncertainty estimator. International Journal of Robust and Nonlinear Control, 27(10), 1826-1840. doi:10.1002/rnc.3639Mondie, S., & Michiels, W. (2003). Finite spectrum assignment of unstable time-delay systems with a safe implementation. IEEE Transactions on Automatic Control, 48(12), 2207-2212. doi:10.1109/tac.2003.820147Zhong, Q.-C. (2004). On Distributed Delay in Linear Control Laws—Part I: Discrete-Delay Implementations. IEEE Transactions on Automatic Control, 49(11), 2074-2080. doi:10.1109/tac.2004.837531Zhou, B., Lin, Z., & Duan, G.-R. (2012). Truncated predictor feedback for linear systems with long time-varying input delays. Automatica, 48(10), 2387-2399. doi:10.1016/j.automatica.2012.06.032Zhou, B., Li, Z.-Y., & Lin, Z. (2013). On higher-order truncated predictor feedback for linear systems with input delay. International Journal of Robust and Nonlinear Control, 24(17), 2609-2627. doi:10.1002/rnc.3012Besançon G Georges D Benayache Z Asymptotic state prediction for continuous-time systems with delayed input and application to control IEEE 2007 Kos, GreeceNajafi, M., Hosseinnia, S., Sheikholeslam, F., & Karimadini, M. (2013). Closed-loop control of dead time systems via sequential sub-predictors. International Journal of Control, 86(4), 599-609. doi:10.1080/00207179.2012.751627Léchappé V Moulay E Plestan F Dynamic observation-prediction for LTI systems with a time-varying delay in the input IEEE 2016 Las Vegas, NVCacace, F., Conte, F., Germani, A., & Pepe, P. (2016). 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    Robustness analysis of discrete predictor-based controllers for input-delay systems

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    In this article, robustness to model uncertainties are analysed in the context of discrete predictor-based state-feedback controllers for discrete-time input-delay systems with time-varying delay, in an LMI framework. The goal is comparing robustness of predictor-based strategies with respect to other (sub)optimal state feedback ones. A numerical example illustrates that improvements in tolerance to modelling errors can be achieved by using the predictor framework.The authors are grateful for grant nos. DPI2008-06737-C02-01, DPI2008-06731-C02-01, DPI2011-27845-C02-01 and PROMETEO/2008/088 from the Spanish and Valencian governments.González Sorribes, A.; Sala, A.; García Gil, PJ.; Albertos Pérez, P. (2013). Robustness analysis of discrete predictor-based controllers for input-delay systems. International Journal of Systems Science. 44(2):232-239. https://doi.org/10.1080/00207721.2011.600469S232239442Boukas, E.-K. (2006). 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(2008), ‘Robust Stabilization of Discrete-time Systems with Time-varying Delay: An LMI Approach’,Mathematical Problems in Engineering, 2008, 15 pages (doi:10.1155/2008/875609)Liu, X. G., Tang, M. L., Martin, R. R., & Wu, M. (2006). Delay-dependent robust stabilisation of discrete-time systems with time-varying delay. IEE Proceedings - Control Theory and Applications, 153(6), 689-702. doi:10.1049/ip-cta:20050223Lozano, R., Castillo, P., Garcia, P., & Dzul, A. (2004). Robust prediction-based control for unstable delay systems: Application to the yaw control of a mini-helicopter. Automatica, 40(4), 603-612. doi:10.1016/j.automatica.2003.10.007Manitius, A., & Olbrot, A. (1979). Finite spectrum assignment problem for systems with delays. IEEE Transactions on Automatic Control, 24(4), 541-552. doi:10.1109/tac.1979.1102124Michiels, W., & Niculescu, S.-I. (2003). On the delay sensitivity of Smith Predictors. International Journal of Systems Science, 34(8-9), 543-551. doi:10.1080/00207720310001609057Palmor, Z.J. (1996), ‘Time-delay Compensation – Smith Predictor and Its Modifications’, inThe Control Handbook, ed. W.S. Levine, Boca Raton: CRC Press, pp. 224–237Pan, Y.-J., Marquez, H. J., & Chen, T. (2006). Stabilization of remote control systems with unknown time varying delays by LMI techniques. International Journal of Control, 79(7), 752-763. doi:10.1080/00207170600654554Richard, J.-P. (2003). Time-delay systems: an overview of some recent advances and open problems. Automatica, 39(10), 1667-1694. doi:10.1016/s0005-1098(03)00167-5Wang, Q.-G., Lee, T. H., & Tan, K. K. (1999). Finite-Spectrum Assignment for Time-Delay Systems. Lecture Notes in Control and Information Sciences. doi:10.1007/978-1-84628-531-8He, Y., Wu, M., Han, Q.-L., & She, J.-H. (2008). Delay-dependentH∞control of linear discrete-time systems with an interval-like time-varying delay. 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