Relevant bibliographies by topics / Hammerstein model

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Hammerstein model'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 July 2025

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Journal articles on the topic "Hammerstein model"

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Liutkevičius, R. "Fuzzy Hammerstein Model of Nonlinear Plant." Nonlinear Analysis: Modelling and Control 13, no. 2 (2008): 201–12. http://dx.doi.org/10.15388/na.2008.13.2.14580.

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This paper presents the synthesis and analysis of the enhanced predictive fuzzy Hammerstein model of the water tank system. Fuzzy Hammerstein model was compared with three other fuzzy models: the first was synthesized using Mamdani type rule base, the second – Takagi-Sugeno type rule base and the third – composed of Mamdani and Takagi-Sugeno rule bases. The synthesized model is invertible so it can be used in the model based control. The fuzzy Hammerstein model was synthesized to eliminate disadvantages of the other fuzzy models. The advantage of the fuzzy Hammerstein model was experimentally
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Mohd, Ashraf Ahmad, Musa Zulkifli, Helmi Suid Mohd, and Zaidi Mohd Tumari Mohd. "Grey wolf optimizer for identification of liquid slosh behavior using continuous-time Hammerstein model." Bulletin of Electrical Engineering and Informatics 9, no. 2 (2020): 542–49. https://doi.org/10.11591/eei.v9i2.2074.

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This paper presents the identification of liquid slosh plant using the Hammerstein model based on Grey Wolf Optimizer (GWO) method. A remote car that carrying a container of liquid is considered as the liquid slosh experimental rig. In contrast to other research works, this paper consider a piece-wise affine function in the nonlinear function of the Hammerstein model, which is more generalized function. Moreover, a continuous-time transfer function is utilized in the Hammerstein model, which is more suitable to represent a real system. The GWO method is used to tune both coefficients in the no
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Jinxing, Shen, Cui Hongxin, Feng Ke, Zhang Hong, and Li Huanliang. "Parameter Identification and Control Algorithm of Electrohydraulic Servo System for Robotic Excavator Based on Improved Hammerstein Model." Mathematical Problems in Engineering 2020 (May 23, 2020): 1–9. http://dx.doi.org/10.1155/2020/9216019.

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In view of the nonlinearity and time-varying characteristics of the electrohydraulic servo system of the robotic excavator, a nonlinear adaptive identification and control algorithm based on improved Hammerstein model is proposed. The Hammerstein algorithm model can approximate the nonlinear system with enough precision, but for the time-varying systems is not satisfactory. In order to compensate for the influence of time-varying factors, the fuzzy control module is designed to adaptively update the forgetting factor. The experimental results show that the improved Hammerstein model error is a
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Fruzzetti, K. P., A. Palazoğlu, and K. A. McDonald. "Nolinear model predictive control using Hammerstein models." Journal of Process Control 7, no. 1 (1997): 31–41. http://dx.doi.org/10.1016/s0959-1524(97)80001-b.

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Teng, Qin, Jian Bo Zhang, and Peng An. "Dynamic Modeling for a Non-Linear System Based on the MOESP Algorithm." Applied Mechanics and Materials 164 (April 2012): 467–72. http://dx.doi.org/10.4028/www.scientific.net/amm.164.467.

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In order to measure accurately air fuel ratio in the engine exhaust gas, the Hammerstein model of the exhaust gas oxygen (EGO) sensor was identified using the multivariable output error state space (MOESP) algorithm. Firstly, a static model of the EGO sensor was identified based on engine experiment data as a static nonlinear part of the Hammerstein model. Then, the MOESP algorithm was used to build a state space model (SSM) of dynamic linear part of the Hammerstein model. To estimate model order, the Akaike Information Criterion (AIC) and the Minimum Description Length (MDL) criterion were co
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Porkuian, Olga, Vladimir Morkun, Natalia Morkun, and Oleksandra Serdyuk. "Predictive Control of the Iron Ore Beneficiation Process Based on the Hammerstein Hybrid Model." Acta Mechanica et Automatica 13, no. 4 (2019): 262–70. http://dx.doi.org/10.2478/ama-2019-0036.

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Abstract Non-linear, dynamic, non-stationary properties characterize objects of the iron ore beneficiation line. Therefore, for their approximation, it is advisable to use models of the Hammerstein class. As a result of comparing the three models of Hammerstein: simple, parallel and recursive-parallel, it was shown that the best result for identifying the considered processes of magnetic beneficiation of iron ore by the minimum error criterion was obtained using the Hammerstein recursive-parallel model. Hence, it is recommended for the identification of beneficiation production objects.
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Qin, Ke, and Jing Chen. "Parameters Identification of Dual-Rate Hammerstein Systems Based on Finite Input Response Models." Applied Mechanics and Materials 204-208 (October 2012): 4742–45. http://dx.doi.org/10.4028/www.scientific.net/amm.204-208.4742.

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This paper studies the parameter estimation for dual-rate Hammerstein systems. The finite input response model is used to approximate the dual-rate Hammerstein systems, and a recursive least squares algorithm is derived to estimate the parameters of the finite input response model. Based on the estimated parameters, the origin parameters of the dual-rate Hammerstein systems can be obtained. An example is provided to show the effectiveness of the proposed method.
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Huang, Ai Qin, and Yong Wang. "The Hammerstein Predict Model of Control Valve Based on Least Square Support Vector Machine." Applied Mechanics and Materials 472 (January 2014): 164–70. http://dx.doi.org/10.4028/www.scientific.net/amm.472.164.

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Control valve is a kind of essential terminal control component controlling the parameters of fluid such as flow and pressure in process-control. However it is a complex nonlinear, multi-input and single-output (MISO) system that is hard to model by traditional methodologies. To establish the pressure model of control valve, this paper presents a Hammerstein modeling method based on the least squares support vector machines (LS-SVM). The linear model parameters and the static nonlinearity of Hammerstein model can be obtained simultaneously by solving a set of linear equations followed by the s
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Zhang, Shuo, Dongqing Wang, and Yaru Yan. "Instrumental Variable-Based OMP Identification Algorithm for Hammerstein Systems." Complexity 2018 (July 22, 2018): 1–10. http://dx.doi.org/10.1155/2018/8420426.

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Hammerstein systems are formed by a static nonlinear block followed by a dynamic linear block. To solve the parameterizing difficulty caused by parameter coupling between the nonlinear part and the linear part in a Hammerstein system, an instrumental variable method is studied to parameterize the Hammerstein system. To achieve in simultaneously identifying parameters and orders of the Hammerstein system and to promote the computational efficiency of the identification algorithm, a sparsity-seeking orthogonal matching pursuit (OMP) optimization method of compressive sensing is extended to ident
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Yu, Hongshan, Jinzhu Peng, and Yandong Tang. "Identification of Nonlinear Dynamic Systems Using Hammerstein-Type Neural Network." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/959507.

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Hammerstein model has been popularly applied to identify the nonlinear systems. In this paper, a Hammerstein-type neural network (HTNN) is derived to formulate the well-known Hammerstein model. The HTNN consists of a nonlinear static gain in cascade with a linear dynamic part. First, the Lipschitz criterion for order determination is derived. Second, the backpropagation algorithm for updating the network weights is presented, and the stability analysis is also drawn. Finally, simulation results show that HTNN identification approach demonstrated identification performances.
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Dissertations / Theses on the topic "Hammerstein model"

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Bezerra, Gabriel Ribeiro. "Modeling and control of The DC-DC Buck-Boost converter using parametric identification techniques." Universidade Federal do CearÃ, 2015. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=14745.

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CoordenaÃÃo de AperfeÃoamento de Pessoal de NÃvel Superior<br>This work presents procedures for modeling a Buck-Boost converter based on offline parametric identification techniques, with employment of black box and gray box models. For the identification of the control-to-output-voltage transfer function, the nonlinear Hammerstein model is employed, a particularly interesting structure to identify DC-DC converters for its ability to incorporate nonlinear static characteristic aside from the dynamic behavior of the plant. The identification of the mentioned transfer function is achieved from i
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Zambrano, Abad Julio Cesar. "Identification of nonlinear processes based on Wiener-Hammerstein models and heuristic optimization." Doctoral thesis, Universitat Politècnica de València, 2021. http://hdl.handle.net/10251/171739.

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[ES] En muchos campos de la ingeniería los modelos matemáticos son utilizados para describir el comportamiento de los sistemas, procesos o fenómenos. Hoy en día, existen varias técnicas o métodos que pueden ser usadas para obtener estos modelos. Debido a su versatilidad y simplicidad, a menudo se prefieren los métodos de identificación de sistemas. Por lo general, estos métodos requieren la definición de una estructura y la estimación computacional de los parámetros que la componen utilizando un conjunto de procedimientos y mediciones de las señales de entrada y salida del sistema. En el conte
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Casillo, Danielle Simone da Silva. "Controle preditivo n?o linear baseado no modelo de Hammerstein com prova de estabilidade." Universidade Federal do Rio Grande do Norte, 2009. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15130.

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Made available in DSpace on 2014-12-17T14:54:52Z (GMT). No. of bitstreams: 1 DanielleSSC.pdf: 1582089 bytes, checksum: 60ca15361e82c560b730f3d2c8f4b062 (MD5) Previous issue date: 2009-03-27<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior<br>The Predictive Controller has been receiving plenty attention in the last decades, because the need to understand, to analyze, to predict and to control real systems has been quickly growing with the technological and industrial progress. The objective of this thesis is to present a contribution for the development and implementation of N
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Ogbonna, Emmanuel. "A multi-parameter empirical model for mesophilic anaerobic digestion." Thesis, University of Hertfordshire, 2017. http://hdl.handle.net/2299/17467.

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Anaerobic digestion, which is the process by which bacteria breakdown organic matter to produce biogas (renewable energy source) and digestate (biofertiliser) in the absence of oxygen, proves to be the ideal concept not only for sustainable energy provision but also for effective organic waste management. However, the production amount of biogas to keep up with the global demand is limited by the underperformance in the system implementing the AD process. This underperformance is due to the difficulty in obtaining and maintaining the optimal operating parameters/states for anaerobic bacteria t
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Park, Junho. "Nonlinear Model Predictive Control for a Managed Pressure Drilling with High-Fidelity Drilling Simulators." BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/6792.

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The world's energy demand has been rapidly increasing and is projected to continue growing for at least the next two decades. With increasing global energy demand and competition from renewable energy, the oil and gas industry is striving for more efficient petroleum production. Many technical breakthroughs have enabled the drilling industry to expand the exploration to more difficult drilling such as deepwater drilling and multilateral directional drilling. For example, managed pressure drilling (MPD) offers ceaseless operation with multiple manipulated variables (MV) and wired drill pipe (WD
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Otoupalík, Petr. "Simulace analogových hudebních efektů pomocí nelineárních filtrů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-218297.

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This thesis deals with a simulation of analogue audio effects using the nonlinear models that replace the analogue nonlinear devices in discrete domain. The thesis describes Volterra system model and simplified Volterra system model that can be realized in two ways, either Wiener model, or Hammerstein model. The method for the analysis and modeling of audio and acoustic nonlinear systems is presented in this thesis. This method allows through knowledge of the input swept-sine signal and the response of the analogue nonlinear system to the input signal to determine the coefficients of the discr
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Peng, Hui. "Quelques résultats sur la réduction spatiale et la commande robuste d’un procédé d’adsorption modulée en pression." Thesis, Lyon 1, 2011. http://www.theses.fr/2011LYO10034.

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Dans cette thèse, nous nous intéressons à la modélisation, la simulation et la commande d'un procédé d'adsorption modulée en pression (procédé PSA). Ces procédés PSA sont des procédés cycliques alternant phase d'adsorption et phase de désorption. Les modèles de ces procédés sont en général décrits par des équations au dérivées partielles qui suivant les modèles décrivent les dynamiques lentes et rapides. Nous avons étudié la modélisation d'un procédé basé sur deux colonnes avec l'utilisation d'un adsorbant monodisperse. Nous proposons un modèle classique qui décrit les quatre phases du cycle d
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Cerqueira, Auciomar Carlos Teixeira de. "Estima??o e compensa??o de n?o linearidades inerentes aos atuadores dos processos industriais." Universidade Federal do Rio Grande do Norte, 2009. http://repositorio.ufrn.br:8080/jspui/handle/123456789/12916.

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Made available in DSpace on 2014-12-17T14:08:38Z (GMT). No. of bitstreams: 1 AuciomarCTC_DISSERT.pdf: 1704122 bytes, checksum: fe303bbcf110f6668682831da2f3480d (MD5) Previous issue date: 2009-12-16<br>The oscillations presents in control loops can cause damages in petrochemical industry. Canceling, or even preventing such oscillations, would save up to large amount of dollars. Studies have identified that one of the causes of these oscillations are the nonlinearities present on industrial process actuators. This study has the objective to develop a methodology for removal of the harmful effe
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Sousa, Leonardo Cheles. "Modelo de histerese para ferrites de potência." reponame:Repositório Institucional da UFABC, 2018.

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Orientador: Prof. Dr. Luiz Alberto Luz de Almeida<br>Coorientador: Prof. Dr. Carlos Eduardo Capovilla<br>Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Elétrica, Santo André, 2018.<br>O trabalho apresenta uma extensao da limitacao estatica Loop Proximity (..2..) do modelo de histerese para incorporar a componente reversivel de magnetizacao dependente de taxa para modelar nucleos de ferrite de energia e, possivelmente, materiais ferromagneticos baseados em ferro e niquel para aplicacoes de baixa frequencia. O modelo proposto e baseado em a combinac
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Anaya, Munoz Víctor Hugo Verfasser], Peter [Akademischer Betreuer] [Hammerstein, Hans-Jörg [Akademischer Betreuer] Rheinberger, and Daniel Piñero [Akademischer Betreuer] Dalmau. "A theoretical model on the role of lateral gene transfer in the evolution of endosymbiotic genomes / Víctor Hugo Anaya Munoz. Gutachter: Peter Hammerstein ; Hans-Jörg Rheinberger ; Daniel Piñero Dalmau." Berlin : Humboldt Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2012. http://d-nb.info/1019165677/34.

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Books on the topic "Hammerstein model"

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Boyd, Melinda. The Politics of Color in Oscar Hammerstein’s Carmen Jones. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252036781.003.0011.

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This chapter explores the politics of color in Oscar Hammerstein's Carmen Jones by focusing on the various layers of representation in its stage and film versions. Carmen Jones uses lyrics that adopt common clichés of Negro speech and equates Georges Bizet's sexually liberated gypsy in Carmen with a lower-class African American woman. After providing a background on the circumstances, precedents, and models that inspired Hammerstein's conception of Carmen Jones, the chapter considers Hammerstein's transformation of the plot and his text-translation practice, along with the opera's exoticism, s
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Book chapters on the topic "Hammerstein model"

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Mete, Selcuk, Hasan Zorlu, and Saban Ozer. "An Improved Hammerstein Model for System Identification." In Information Innovation Technology in Smart Cities. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-1741-4_4.

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Wellers, Matthias, and Heinrich Rake. "Nonlinear Model Predictive Control Based on Stable Wiener and Hammerstein Models." In Nonlinear Model Predictive Control. Birkhäuser Basel, 2000. http://dx.doi.org/10.1007/978-3-0348-8407-5_20.

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Abonyi, Janos, Robert Babuska, Ferenc Szeifert, Lajos Nagy, and Henk Verbruggen. "Design and Application of Block-Oriented Fuzzy Models — Fuzzy Hammerstein Model." In Soft Computing in Industrial Applications. Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0509-1_7.

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Al-Duwaish, Hussain N., and Syed Saad Azhar Ali. "Hammerstein Model Identification Using Radial Basis Functions Neural Networks." In Artificial Neural Networks — ICANN 2001. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44668-0_131.

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Cuevas, Erik, Primitivo Diaz, and Octavio Camarena. "ANFIS-Hammerstein Model for Nonlinear Systems Identification Using GSA." In Intelligent Systems Reference Library. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58100-8_5.

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Jia, Li, Xunlong Li, and Min-Sen Chiu. "Identification of MIMO Neuro-fuzzy Hammerstein Model with Noises." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45283-7_31.

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Bai, Er-Wei. "A Blind Approach to the Hammerstein-Wiener Model Identification." In Lecture Notes in Control and Information Sciences. Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-513-2_19.

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Hong, Man, and Shao Cheng. "Hammerstein-Wiener Model Predictive Control of Continuous Stirred Tank Reactor." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21697-8_30.

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Bai, Er-Wei. "Decoupling the Linear and Nonlinear Parts in Hammerstein Model Identification." In Lecture Notes in Control and Information Sciences. Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-513-2_20.

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Li, Junhao, Fukai Zhang, Cong Wang, and Yuehu Liu. "Identification of Wiener-Hammerstein Model Using Stochastic Variational Bayesian Learning." In Lecture Notes in Computer Science. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-0783-9_11.

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Conference papers on the topic "Hammerstein model"

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Kouadio, Kouao Laurent, and Pierre Claver Bizimana. "Adaptive Hammerstein- Wiener Model for Intelligent Networks." In 2024 International Conference on Intelligent Computing and Next Generation Networks (ICNGN). IEEE, 2024. https://doi.org/10.1109/icngn63705.2024.10871420.

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Long, Jianrui, and Geoffrey A. Williamson. "Parametric Hammerstein-Wiener model estimation via dual Hammerstein identification." In 2013 IEEE Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE). IEEE, 2013. http://dx.doi.org/10.1109/dsp-spe.2013.6642565.

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Mete, Selcuk, Saban Ozer, and Hasan Zorlu. "System identification using Hammerstein model." In 2014 22nd Signal Processing and Communications Applications Conference (SIU). IEEE, 2014. http://dx.doi.org/10.1109/siu.2014.6830476.

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Thieme, Ethan. "Behavioral Models of Differential Amplifiers with Hammerstein Model." In 2024 ECE Undergraduate Research Symposium - Urbana, Illinois, United States of America - April - 2024. US DOE, 2024. https://doi.org/10.2172/2563885.

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Feng Wang, Keyi Xing, Xiaoping Xu, and Huixia Liu. "An identification approach of Hammerstein model." In 2010 Chinese Control and Decision Conference (CCDC). IEEE, 2010. http://dx.doi.org/10.1109/ccdc.2010.5498966.

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Zhang, Jianghuai, and Zhong Zhao. "Learning-Based Model Predictive Control with Hammerstein Model." In 2023 42nd Chinese Control Conference (CCC). IEEE, 2023. http://dx.doi.org/10.23919/ccc58697.2023.10241119.

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"SLIDING MODE CONTROL FOR HAMMERSTEIN MODEL BASED ON MPC." In 4th International Conference on Informatics in Control, Automation and Robotics. SciTePress - Science and and Technology Publications, 2007. http://dx.doi.org/10.5220/0001639402320237.

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Khan, Ali Umair, and Muhammad Bilal Kadri. "MPC of Hammerstein model with evolving fuzzy." In 2012 International Conference on Emerging Technologies (ICET). IEEE, 2012. http://dx.doi.org/10.1109/icet.2012.6375448.

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Lin, Lin, Weixing Lin, Haizhen Yu, and Xuhua Shi. "PSO Hammerstein Model Based PM2.5 Concentration Forecasting." In 2018 13th World Congress on Intelligent Control and Automation (WCICA). IEEE, 2018. http://dx.doi.org/10.1109/wcica.2018.8630521.

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Wang, Feng, Keyi Xing, Xiaoping Xu, Huixia Liu, and Xiaojing Sun. "Research on identification algorithm of Hammerstein model." In 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA). IEEE, 2010. http://dx.doi.org/10.1109/bicta.2010.5645355.

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Reports on the topic "Hammerstein model"

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An Input Linearized Powertrain Model for the Optimal Control of Hybrid Electric Vehicles. SAE International, 2022. http://dx.doi.org/10.4271/2022-01-0741.

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Models of hybrid powertrains are used to establish the best combination of conventional engine power and electric motor power for the current driving situation. The model is characteristic for having two control inputs and one output constraint: the total torque should be equal to the torque requested by the driver. To eliminate the constraint, several alternative formulations are used, considering engine power or motor power or even the ratio between them as a single control input. From this input and the constraint, both power levels can be deduced. There are different popular choices for th
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