3,400 research outputs found

    Sliding Mode Reference Coordination of Constrained Feedback Systems

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    [EN] This paper addresses the problem of coordinating dynamical systems with possibly different dynamics (e.g., linear and nonlinear, different orders, constraints, etc.) to achieve some desired collective behavior under the constraints and capabilities of each system. To this end, we develop a new methodology based on reference conditioning techniques using geometric set invariance and sliding mode control: the sliding mode reference coordination (SMRCoord). The main idea is to coordinate the systems references. Starting from a general framework, we propose two approaches: a local one through direct interactions between the different systems by sharing and conditioning their own references and a global centralized one, where a central node makes decisions using information coming from the systems references. In particular, in this work we focus in implementation on multivariable systems like unmanned aerial vehicles (UAVs) and robustness to external perturbations. To show the applicability of the approach, the problem of coordinating UAVs with input constraints is addressed as a particular case of multivariable reference coordination with both global and local configuration.Research in this area is partially supported by Argentine government (ANPCyT PICT 2011-0888 and CONICET PIP 112-2011-00361), Spanish government (FEDER-CICYT DPI2011-28112-C04-01), and Universitat Politecnica de Valencia (Grant FPI/2009-21)Vignoni, A.; Garelli, F.; Picó, J. (2013). Sliding Mode Reference Coordination of Constrained Feedback Systems. Mathematical Problems in Engineering. 2013:1-11. https://doi.org/10.1155/2013/764348S1112013Information consensus in multivehicle cooperative control. (2007). IEEE Control Systems, 27(2), 71-82. doi:10.1109/mcs.2007.338264Cao, Y., Yu, W., Ren, W., & Chen, G. (2013). An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination. IEEE Transactions on Industrial Informatics, 9(1), 427-438. doi:10.1109/tii.2012.2219061Interconnected dynamic systems: An overview on distributed control. (2013). IEEE Control Systems, 33(1), 76-88. doi:10.1109/mcs.2012.2225929Olfati-Saber, R., Fax, J. A., & Murray, R. M. (2007). Consensus and Cooperation in Networked Multi-Agent Systems. Proceedings of the IEEE, 95(1), 215-233. doi:10.1109/jproc.2006.887293He, W., & Cao, J. (2011). Consensus control for high-order multi-agent systems. IET Control Theory & Applications, 5(1), 231. doi:10.1049/iet-cta.2009.0191Liu, L. (2012). Robust cooperative output regulation problem for non-linear multi-agent systems. IET Control Theory & Applications, 6(13), 2142-2148. doi:10.1049/iet-cta.2011.0575Pitarch, J. L., Sala, A., & Arino, C. V. (2014). Closed-Form Estimates of the Domain of Attraction for Nonlinear Systems via Fuzzy-Polynomial Models. IEEE Transactions on Cybernetics, 44(4), 526-538. doi:10.1109/tcyb.2013.2258910Nuñez, S., De Battista, H., Garelli, F., Vignoni, A., & Picó, J. (2013). Second-order sliding mode observer for multiple kinetic rates estimation in bioprocesses. Control Engineering Practice, 21(9), 1259-1265. doi:10.1016/j.conengprac.2013.03.003Wu, L., Su, X., & Shi, P. (2012). Sliding mode control with bounded gain performance of Markovian jump singular time-delay systems. Automatica, 48(8), 1929-1933. doi:10.1016/j.automatica.2012.05.064Cao, Y., Ren, W., & Meng, Z. (2010). Decentralized finite-time sliding mode estimators and their applications in decentralized finite-time formation tracking. Systems & Control Letters, 59(9), 522-529. doi:10.1016/j.sysconle.2010.06.002Cortés, J. (2006). Finite-time convergent gradient flows with applications to network consensus. Automatica, 42(11), 1993-2000. doi:10.1016/j.automatica.2006.06.015Rao, S., & Ghose, D. (2011). Sliding mode control-based algorithms for consensus in connected swarms. International Journal of Control, 84(9), 1477-1490. doi:10.1080/00207179.2011.602834Guo, P., Zhang, J., Lyu, M., & Bo, Y. (2013). Sliding Mode Control for Multiagent System with Time-Delay and Uncertainties: An LMI Approach. Mathematical Problems in Engineering, 2013, 1-12. doi:10.1155/2013/805492Garelli, F., Mantz, R. J., & De Battista, H. (2006). Limiting interactions in decentralized control of MIMO systems. Journal of Process Control, 16(5), 473-483. doi:10.1016/j.jprocont.2005.09.001Garelli, F., Mantz, R. J., & De Battista, H. (2007). Sliding mode compensation to preserve dynamic decoupling of stable systems. Chemical Engineering Science, 62(17), 4705-4716. doi:10.1016/j.ces.2007.05.020Picó, J., Garelli, F., De Battista, H., & Mantz, R. J. (2009). Geometric invariance and reference conditioning ideas for control of overflow metabolism. Journal of Process Control, 19(10), 1617-1626. doi:10.1016/j.jprocont.2009.08.007Revert, A., Garelli, F., Pico, J., De Battista, H., Rossetti, P., Vehi, J., & Bondia, J. (2013). Safety Auxiliary Feedback Element for the Artificial Pancreas in Type 1 Diabetes. IEEE Transactions on Biomedical Engineering, 60(8), 2113-2122. doi:10.1109/tbme.2013.2247602Gracia, L., Sala, A., & Garelli, F. (2012). A supervisory loop approach to fulfill workspace constraints in redundant robots. Robotics and Autonomous Systems, 60(1), 1-15. doi:10.1016/j.robot.2011.07.008Gracia, L., Garelli, F., & Sala, A. (2013). Integrated sliding-mode algorithms in robot tracking applications. Robotics and Computer-Integrated Manufacturing, 29(1), 53-62. doi:10.1016/j.rcim.2012.07.007Vignoni, A., Garelli, F., & Picó, J. (2013). Coordinación de sistemas con diferentes dinámicas utilizando conceptos de invarianza geométrica y modos deslizantes. Revista Iberoamericana de Automática e Informática Industrial RIAI, 10(4), 390-401. doi:10.1016/j.riai.2013.09.001Hanus, R., Kinnaert, M., & Henrotte, J.-L. (1987). Conditioning technique, a general anti-windup and bumpless transfer method. Automatica, 23(6), 729-739. doi:10.1016/0005-1098(87)90029-xMareczek, J., Buss, M., & Spong, M. W. (2002). Invariance control for a class of cascade nonlinear systems. IEEE Transactions on Automatic Control, 47(4), 636-640. doi:10.1109/9.995041Blasco, X., García-Nieto, S., & Reynoso-Meza, G. (2012). Control autónomo del seguimiento de trayectorias de un vehículo cuatrirrotor. Simulación y evaluación de propuestas. Revista Iberoamericana de Automática e Informática Industrial RIAI, 9(2), 194-199. doi:10.1016/j.riai.2012.01.00

    Variance-constrained multiobjective control and filtering for nonlinear stochastic systems: A survey

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    The multiobjective control and filtering problems for nonlinear stochastic systems with variance constraints are surveyed. First, the concepts of nonlinear stochastic systems are recalled along with the introduction of some recent advances. Then, the covariance control theory, which serves as a practical method for multi-objective control design as well as a foundation for linear system theory, is reviewed comprehensively. The multiple design requirements frequently applied in engineering practice for the use of evaluating system performances are introduced, including robustness, reliability, and dissipativity. Several design techniques suitable for the multi-objective variance-constrained control and filtering problems for nonlinear stochastic systems are discussed. In particular, as a special case for the multi-objective design problems, the mixed H 2 / H ∞ control and filtering problems are reviewed in great detail. Subsequently, some latest results on the variance-constrained multi-objective control and filtering problems for the nonlinear stochastic systems are summarized. Finally, conclusions are drawn, and several possible future research directions are pointed out

    Analysis, filtering, and control for Takagi-Sugeno fuzzy models in networked systems

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    Copyright © 2015 Sunjie Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple dynamic structure as well as its capability of approximating any smooth nonlinear function to any specified accuracy within any compact set. In terms of such a model, the performance analysis and the design of controllers and filters play important roles in the research of fuzzy systems. In this paper, we aim to survey some recent advances on the T-S fuzzy control and filtering problems with various network-induced phenomena. The network-induced phenomena under consideration mainly include communication delays, packet dropouts, signal quantization, and randomly occurring uncertainties (ROUs). With such network-induced phenomena, the developments on T-S fuzzy control and filtering issues are reviewed in detail. In addition, some latest results on this topic are highlighted. In the end, conclusions are drawn and some possible future research directions are pointed out.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 11301118 and 61174136, the Natural Science Foundation of Jiangsu Province of China under Grant BK20130017, the Fundamental Research Funds for the Central Universities of China under Grant CUSF-DH-D-2013061, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

    Time-and event-driven communication process for networked control systems: A survey

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    Copyright © 2014 Lei Zou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In recent years, theoretical and practical research topics on networked control systems (NCSs) have gained an increasing interest from many researchers in a variety of disciplines owing to the extensive applications of NCSs in practice. In particular, an urgent need has arisen to understand the effects of communication processes on system performances. Sampling and protocol are two fundamental aspects of a communication process which have attracted a great deal of research attention. Most research focus has been on the analysis and control of dynamical behaviors under certain sampling procedures and communication protocols. In this paper, we aim to survey some recent advances on the analysis and synthesis issues of NCSs with different sampling procedures (time-and event-driven sampling) and protocols (static and dynamic protocols). First, these sampling procedures and protocols are introduced in detail according to their engineering backgrounds as well as dynamic natures. Then, the developments of the stabilization, control, and filtering problems are systematically reviewed and discussed in great detail. Finally, we conclude the paper by outlining future research challenges for analysis and synthesis problems of NCSs with different communication processes.This work was supported in part by the National Natural Science Foundation of China under Grants 61329301, 61374127, and 61374010, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

    Disturbance Observer-based Robust Control and Its Applications: 35th Anniversary Overview

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    Disturbance Observer has been one of the most widely used robust control tools since it was proposed in 1983. This paper introduces the origins of Disturbance Observer and presents a survey of the major results on Disturbance Observer-based robust control in the last thirty-five years. Furthermore, it explains the analysis and synthesis techniques of Disturbance Observer-based robust control for linear and nonlinear systems by using a unified framework. In the last section, this paper presents concluding remarks on Disturbance Observer-based robust control and its engineering applications.Comment: 12 pages, 4 figure
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