Academic literature on the topic 'Input-constrained systems'
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Journal articles on the topic "Input-constrained systems"
Soroush, Masoud, Sairam Valluri, and Nasir Mehranbod. "Nonlinear control of input-constrained systems." Computers & Chemical Engineering 30, no. 1 (November 2005): 158–81. http://dx.doi.org/10.1016/j.compchemeng.2005.08.013.
Full textHägg, Per, Christian A. Larsson, Afrooz Ebadat, Bo Wahlberg, and Häkan Hjalmarsson. "Input Signal Generation for Constrained Multiple-Input Multple-Output Systems." IFAC Proceedings Volumes 47, no. 3 (2014): 1410–15. http://dx.doi.org/10.3182/20140824-6-za-1003.02289.
Full textPark, Bong Seok, Jae Young Lee, Jin Bae Park, and Yoon Ho Choi. "Adaptive control for input-constrained linear systems." International Journal of Control, Automation and Systems 10, no. 5 (September 30, 2012): 890–96. http://dx.doi.org/10.1007/s12555-012-0504-4.
Full textAbel, Imoleayo, Mrdjan Jankovic, and Miroslav Krstić. "Constrained Stabilization of Multi-Input Linear Systems with Distinct Input Delays." IFAC-PapersOnLine 52, no. 2 (2019): 82–87. http://dx.doi.org/10.1016/j.ifacol.2019.08.015.
Full textYuanyuan, Tu, Wang Dayi, and Li Wenbo. "Reconfigurability evaluation method for input-constrained control systems." Journal of Systems Engineering and Electronics 32, no. 5 (October 2021): 1023–30. http://dx.doi.org/10.23919/jsee.2021.000087.
Full textChen, Tianshi, Zhiyuan Liu, Hong Chen, and Run Pei. "CONSTRAINED INPUT-TO-STATE STABILITY OF NONLINEAR SYSTEMS." IFAC Proceedings Volumes 38, no. 1 (2005): 318–23. http://dx.doi.org/10.3182/20050703-6-cz-1902.00707.
Full textd'Alessandro, P., and E. De Santis. "Reachability in input constrained discrete-time linear systems." Automatica 28, no. 1 (January 1992): 227–29. http://dx.doi.org/10.1016/0005-1098(92)90026-c.
Full textKUBRUSLY, C. S., and P. C. M. VIEIRA. "Constrained-Input Constrained-State Stability in a Banach Space." IMA Journal of Mathematical Control and Information 7, no. 2 (1990): 113–24. http://dx.doi.org/10.1093/imamci/7.2.113.
Full textNandi, Souransu, and Tarunraj Singh. "Joint chance constrained input shaping." Journal of the Franklin Institute 357, no. 14 (September 2020): 10027–53. http://dx.doi.org/10.1016/j.jfranklin.2020.07.044.
Full text唐, 丽. "Constrained Control for Strict Feedback Systems with Input Saturation." Modeling and Simulation 08, no. 03 (2019): 102–16. http://dx.doi.org/10.12677/mos.2019.83013.
Full textDissertations / Theses on the topic "Input-constrained systems"
Demenkov, Maxim. "Geometric algorithms for input constrained systems with application to flight control." Thesis, De Montfort University, 2007. http://hdl.handle.net/2086/4950.
Full textYi, Xinlei. "Resource-Constrained Multi-Agent Control Systems: Dynamic Event-triggering, Input Saturation, and Connectivity Preservation." Licentiate thesis, KTH, Reglerteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-216951.
Full textQC 20171025
Ghazali, Abu Baker MHD. "Advanced controllers for building energy management systems. Advanced controllers based on traditional mathematical methods (MIMO P+I, state-space, adaptive solutions with constraints) and intelligent solutions (fuzzy logic and genetic algorithms) are investigated for humidifying, ventilating and air-conditioning applications." Thesis, University of Bradford, 1996. http://hdl.handle.net/10454/4197.
Full textMahmood, Khalid. "Constrained linear and non-linear adaptive equalization techniques for MIMO-CDMA systems." Thesis, De Montfort University, 2013. http://hdl.handle.net/2086/10203.
Full textFlila, Saïda. "Identification optimale et commande prédictive : applications en génie des procédés." Phd thesis, Université Claude Bernard - Lyon I, 2010. http://tel.archives-ouvertes.fr/tel-00458661.
Full textBen, Zid Maha. "Emploi de techniques de traitement de signal MIMO pour des applications dédiées réseaux de capteurs sans fil." Thesis, Grenoble, 2012. http://www.theses.fr/2012GRENT017/document.
Full textThe aim of this work is to study from a signal processing point of view the use of MIMO (Multiple Input Multiple Output) communication systems for algorithms dedicated to wireless sensor networks. We investigate energy-constrained wireless sensor networks and we focus on cluster topology of the network. This topology permits for the use of MIMO communication system model. First, we review different aspects that characterize the wireless sensor network. Then, we introduce the existing strategies for energy conservation in the network. The basic concepts of MIMO systems are presented in the second chapter and numerical results are provided for evaluating the performances of MIMO techniques. Of particular interest, polarization diversity over rich scattering environment is studied. Thereafter, beamforming approach is proposed for the development of an original localization algorithm in wireless sensor network. The novel algorithm is described and performances are evaluated by simulation. We determine the optimal system configuration between a pair of clusters that permits for the highest capacity to energy ratio in the fourth chapter. The final chapter is devoted to sensor nodes selection in wireless sensor network. The aim of using such technique is to make energy conservation in the network
De, Dona Jose A. "Input constrained linear control." Thesis, 2000. http://hdl.handle.net/1959.13/1408362.
Full textThe presence of input constraints is ubiquitous in control systems. As soon as higher performance-eg., faster response-is demanded of the system, limitations imposed by input constraints are more than likely to be encountered. This thesis focuses on various aspects of control system design for linear plants subject to input constraints. For such problems, a number of the results of the well known theory of linear systems still apply, but yet there are many aspects which are of a definitive nonlinear nature, making these problems highly nontrivial. This explains the fact that, despite considerable past work on the topic, there still remain many interesting unsolved research problems. In this thesis we study different control methodologies aimed at dealing with this problem. The main methodologies considered are: model predictive control, time optimal control and switching strategies. Insight is gained through the analysis of the solutions provided by these control formulations. In the case of model predictive control, a technique traditionally implemented via an on-line optimisation, our approach leads us to investigate closed-form solutions to this problem. By obtaining closed-form analytical solutions to model predictive control of limited horizons, we are able to elucidate aspects of the underlying structure of its solution. We also obtain a closed-form solution for arbitrary horizon model predictive control which is, in general, valid locally, in a closed region of the state-space. A common observation that is made in the various control formulations considered in the thesis is that they can be implemented by switching strategies which have similar underlying features. These features are of crucial importance for the achievement of high performance. The specific features of interest are the shape of the switching surface and the degree of effective use of the available control authority. This insight is used to devise switching strategies aimed at achieving high performance. Robustness issues associated with the switching strategies are also addressed.
TESI, PIETRO. "Switching supervisory control: adaptive and input-constrained systems." Doctoral thesis, 2010. http://hdl.handle.net/2158/592008.
Full textHuang, Chien-Hsun, and 黃建勛. "Input Constrained Synthesis of Discrete Nonlinear Passive Systems via Affine T-S Fuzzy Model." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/34234665447773911377.
Full text國立臺灣海洋大學
輪機工程系
95
Abstract In this thesis, we will introduce the passive properties, input constrained and Takagi-Sugeno (T-S) Fuzzy model for stability analysis and controller synthesis. The main idea of passivity theory behind this is that physical systems have certain input-output properties related to the conservation, dissipation and transport of energy. The total energy stored in the system decrease with time. One of key properties of passivity theory, it can use to oppose external disturbance effectively and ensure system stable. In another way, the focus of input constrained theory, to achieve conserve control energy, we use RMS constraints for the variance of the system. The T-S Fuzzy model is similar to nonlinear dynamic system and via several sub-linear systems with the membership function which related of each sub-linear system. Through the Lyapunov stsbility criterion, passivity theory, input constrained theory and Iterative Linear Matrix Inequality (ILMI) algorithm, the problems of stability analysis and controller design are discussed in this thesis. Finally, examples are provided to show the application of the approaches of this thesis. Keywords: Input constraint, Passivity Theory, Affine Takagi-Sugeno Fuzzy Model, Iterative Linear Matrix Inequality, S-Porcedure
Wen-TengHsu and 許文騰. "An Input-Constrained Reduced-Order Observer and NARMAX Model-Based Adaptive Tracker with Fault Tolerance for Unknown Systems with an Input-Output Direct Feed-Through Term." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/11400392290801017705.
Full text國立成功大學
電機工程學系
102
This dissertation proposes an input-constrained reduced-order observer-based adaptive tracker with fault tolerance for unknown nonlinear stochastic systems with an input-output direct feed-through term to obtain good tracking performance. The major contributions of this dissertation are stated as follows: Firstly, realization of causal current output-based optimal full/reduced-order observer and tracker for the linear sampled-data system with a direct transmission term from input to output is newly proposed. Furthermore, the time derivative of the control input existed in the continuous-time reduced-order observer can be avoided in the proposed one for the continuous-time system with an input-output feed-through term. Secondly, an active full-order fault tolerance tracker using the modified nonlinear autoregressive moving average with exogenous inputs (NARMAX) model for state-space self-tuning control (STC) of unknown nonlinear stochastic hybrid systems with a direct transmission term is proposed. For the system identification process, the initial parameters of the modified NARMAX model assigned by the off-line OKID and can speed up the convergence speed of the recursive extended least squares (RELS) method to determine a reliable dynamic model. Moreover, the modified state-space self-tuning control methodology due to the NARMAX model can quickly make an appropriate reaction to the variation of system parameters when the abrupt input fault and/or the gradual input fault occurs. Finally, an input-constrained reduced-order observer-based self-tuner with fault tolerance for unknown nonlinear stochastic systems with an input-output direct feed-through term has been proposed. Some illustrative examples are given to demonstrate the effectiveness of the proposed methodologies.
Books on the topic "Input-constrained systems"
de Almeida, Roberto G., and Ernie Lepore. Semantics for a Module. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190464783.003.0006.
Full textGolan, Amos. Foundations of Info-Metrics. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199349524.001.0001.
Full textBook chapters on the topic "Input-constrained systems"
Aouaouda, Sabrina, Lotfi Moussaoui, and Ines Righi. "Input-Constrained Controller Design for Nonlinear Systems." In Smart Innovation, Systems and Technologies, 240–53. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21009-0_23.
Full textFeng, Gang. "Robust Adaptive Control of Input Rate Constrained Discrete Time Systems." In Adaptive Control of Nonsmooth Dynamic Systems, 333–48. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-3687-3_13.
Full textFu, Junjie, Guanghui Wen, Yongjun Xu, Ali Zemouche, and Fan Zhang. "Resilient Cooperative Control of Input Constrained Networked Cyber-Physical Systems." In Security and Resilience in Cyber-Physical Systems, 267–98. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97166-3_11.
Full textAraújo, José M., and Carlos E. T. Dórea. "Neural Network Fitting for Input-Output Manifolds in Constrained Linear Systems." In Nature-Inspired Computing for Control Systems, 145–67. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26230-7_6.
Full textLiu, Zhilin, Xin Yuan, Jun Zhang, and Li Su. "Robust Control of Piecewise Linear Switched System with Constrained Input and Ellipsoid." In Proceedings of 2016 Chinese Intelligent Systems Conference, 65–77. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2338-5_7.
Full textGrancharova, Alexandra, and Tor A. Johansen. "Explicit Approximate Model Predictive Control of Constrained Nonlinear Systems with Quantized Input." In Nonlinear Model Predictive Control, 371–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01094-1_30.
Full textMaezawa, Akira, Katsutoshi Itoyama, Toru Takahashi, Kazunori Komatani, Tetsuya Ogata, and Hiroshi G. Okuno. "Violin Fingering Estimation Based on Violin Pedagogical Fingering Model Constrained by Bowed Sequence Estimation from Audio Input." In Trends in Applied Intelligent Systems, 249–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13033-5_26.
Full textHuang, Yuzhu, Derong Liu, and Qinglai Wei. "Generalized Hamilton-Jacobi-Isaacs Formulation-Based Neural Network H ∞ Control for Constrained Input Nonlinear Systems." In Neural Information Processing, 218–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34475-6_27.
Full textDong, Hairong, Xiaoyu Wang, Shigen Gao, and Yubing Wang. "Neural Adaptive Dynamic Surface Control of Nonlinear Systems with Partially Constrained Tracking Errors and Input Saturation." In Advances in Neural Networks - ISNN 2017, 20–27. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59081-3_3.
Full textDe Giovanni, Elisabetta, Farnaz Forooghifar, Gregoire Surrel, Tomas Teijeiro, Miguel Peon, Amir Aminifar, and David Atienza Alonso. "Intelligent Edge Biomedical Sensors in the Internet of Things (IoT) Era." In Emerging Computing: From Devices to Systems, 407–33. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7487-7_13.
Full textConference papers on the topic "Input-constrained systems"
Malki, Suleyman, and Lambert Spaanenburg. "Optimization of input-constrained systems." In SPIE Europe Microtechnologies for the New Millennium, edited by Teresa Riesgo, Eduardo de la Torre, and Leandro Soares Indrusiak. SPIE, 2009. http://dx.doi.org/10.1117/12.821905.
Full textAbel, Imoleayo, Mrdjan Janković, and Miroslav Krstić. "Constrained Control of Input Delayed Systems With Partially Compensated Input Delays." In ASME 2020 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/dscc2020-3271.
Full text"Soft tracking control for input constrained systems." In Proceedings of the 1999 American Control Conference. IEEE, 1999. http://dx.doi.org/10.1109/acc.1999.786500.
Full textKHALLOUK, Hamza, and Fouad MESQUINE. "Regional Pole Assignment for Constrained Input Uncertain Systems." In 2018 7th International Conference on Systems and Control (ICSC). IEEE, 2018. http://dx.doi.org/10.1109/icosc.2018.8587782.
Full textHe Kong, Graham Goodwin, and Maria Seron. "Sparse networked control of input constrained linear systems." In 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). IEEE, 2013. http://dx.doi.org/10.1109/cdc.2013.6760936.
Full textAbu-Khalaf, M., F. L. Lewis, and Jie Huang. "Hamilton-Jacobi-Isaacs formulation for constrained input nonlinear systems." In 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601). IEEE, 2004. http://dx.doi.org/10.1109/cdc.2004.1429604.
Full textHara, Naoyuki, and Keiji Konishi. "Parallel model predictive control for input constrained linear systems." In 2016 IEEE 55th Conference on Decision and Control (CDC). IEEE, 2016. http://dx.doi.org/10.1109/cdc.2016.7798614.
Full textAlli-Oke, Razak Olusegun. "A Reference-Optimizing Antiwindup Control for Input-Constrained Systems." In 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2019. http://dx.doi.org/10.1109/codit.2019.8820683.
Full textGiri, F., E. Chater, F. Z. Chaoui, and J. B. Gning. "Further tracking results for input-constrained minimum-phase systems." In 2009 American Control Conference. IEEE, 2009. http://dx.doi.org/10.1109/acc.2009.5159899.
Full textus Saqib, Najam, Muntazir Hussain, Muhammad Siddique, Muhammad Rehan, and Naeem Iqbal. "Static AWC Design for Input Constrained Nonlinear Parameter Varying Systems." In TENCON 2018 - 2018 IEEE Region 10 Conference. IEEE, 2018. http://dx.doi.org/10.1109/tencon.2018.8650373.
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