Relevant bibliographies by topics / Sliding model control

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Sliding model control'

Author: Grafiati
Published: 5 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Sliding model control"

1

Y.P., Patil. "Discrete Adaptive Model Following Sliding Mode Control Design for Improved Performance." Journal of Advanced Research in Dynamical and Control Systems 12, SP3 (2020): 557–69. http://dx.doi.org/10.5373/jardcs/v12sp3/20201293.

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Javadi Moghaddam, Jalal, Ghasem Zarei, Davood Momeni, and Hamideh Faridi. "Non-linear control model for use in greenhouse climate control systems." Research in Agricultural Engineering 68, No. 1 (2022): 9–17. http://dx.doi.org/10.17221/37/2021-rae.

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In this study, a non-linear control system was designed and proposed to control the greenhouse climate conditions. This control system directly uses the information of sensors, installed inside and outside the greenhouse. To design this proposed control system, the principles of a non-linear control system and the concepts of equilibrium points and zero dynamics of system theories were used. To show the capability and applicability of the proposed control system, it was compared with an integral sliding mode controller. A greenhouse with similar climatic conditions was used to simulate the per
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Song, Chonghui. "Optimal Control Algorithm of Constrained Fuzzy System Integrating Sliding Mode Control and Model Predictive Control." Mathematical Problems in Engineering 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/897853.

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The sliding mode control and the model predictive control are connected by the value function of the optimal control problem for constrained fuzzy system. New conditions for the existence and stability of a sliding mode are proposed. Those conditions are more general conditions for the existence and stability of a sliding mode. When it is applied to the controller design, the design procedures are different from other sliding mode control (SMC) methods in that only the decay rate of the sliding mode motion is specified. The obtained controllers are state-feedback model predictive control (MPC)
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Y., P. Patil, and G. Patel H. "Robust Control Design using Discrete Sliding Mode Control for Higher-Order Uncertain Systems." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 3055–63. https://doi.org/10.35940/ijeat.C6037.029320.

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This paper considers a tracking problem on discrete-time higher-order linear time-delay systems. The improved observer-model following sliding mode controller (OMF-SMC) is proposed. The combination uses a classical Luyenberger observer based controller to achieve predefined process output and sliding mode controller is added to assure the robustness despite of uncertainty and external disturbances. To show the effectiveness of proposed method, four error performance indices, maximum peak overshoot and settling time are considered rigorously. The simulations results on the non-oscillatory, mode
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Pan, Shenghu, and Haitao Liu. "Synchronous Control of Two Motors Based on Improved Sliding Mode Control." Academic Journal of Science and Technology 14, no. 1 (2025): 236–42. https://doi.org/10.54097/x3fw4d46.

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With the technological development of the society, permanent magnet synchronous motors are used more and more widely, especially in the two-motor synchronous system. Aiming at the problems of response performance and anti-interference ability of the dual motor synchronous system, this paper proposes an improved sliding mode speed control controller. First, its mathematical model is established by analyzing the mechanical principle and working principle of the permanent magnet synchronous motor. On the basis of the traditional sliding mode controller, the sliding mode surface and convergence ra
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Fallaha, Charles, and Maarouf Saad. "Model-based sliding functions design for sliding mode robot control." International Journal of Modelling, Identification and Control 30, no. 1 (2018): 48. http://dx.doi.org/10.1504/ijmic.2018.10014595.

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Wang, Zheng Jun, Jun Zheng Wang, Hao Wang, and Jiang Bo Zhao. "Model Parameter Adaptive Sliding Mode Model-Following Position Control of PMSM." Advanced Materials Research 466-467 (February 2012): 1089–94. http://dx.doi.org/10.4028/www.scientific.net/amr.466-467.1089.

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This paper aims at improving the robustness of the PMSM position control system with the parameter variation and load disturbance. A novel control strategy utilizing sliding mode model-following control (SMMFC) with the adaptive parameters observed by dual unscented Kalman filter (DUKF) observer is proposed. The switching gain of sliding mode is designed including the observed states of the system to suppress the chattering. The experimental results show that the robustness has been improved by sliding mode control, and the chattering has been well suppressed by switching gain adaptation depen
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Zhao, Bingjie, Yang Liu, Danping Jia, et al. "Application of Fuzzy Sliding Mode Control in Voice Coil Motor Control System." Journal of Physics: Conference Series 2281, no. 1 (2022): 012009. http://dx.doi.org/10.1088/1742-6596/2281/1/012009.

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Abstract The requirements of modern industry on the response speed and accuracy of voice coil motors has been the gradual growth, and PID control algorithms have become increasingly unable to meet their requirements. The use of sliding mode control can speed up the response time of the motor, and it also can improve the response speed, overshoot and instability problems in some degree. However, the sliding mode control algorithm will bring jitter to the entire system. This paper combines fuzzy control and sliding mode control to adjust the parameters of the sliding mode control algorithm in re
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Nugroho, Gesang, and Zahari Taha. "Helicopter Motion Control Using Model-Based Sliding Mode Controller." Journal of Advanced Computational Intelligence and Intelligent Informatics 12, no. 4 (2008): 342–47. http://dx.doi.org/10.20965/jaciii.2008.p0342.

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This paper describes a model-based controller design for helicopter using the sliding mode approach. The controller design assumes that only measured output are available and uses sliding mode observer to estimate all states of the system. The estimated states are then used to construct a model reference sliding mode control law. Simulation shows good performance for lateral velocity, longitudinal velocity, vertical velocity and yaw rate control.
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Liu, Wei, Hui Ye, and Xiaofei Yang. "Model-Free Adaptive Sliding Mode Control Method for Unmanned Surface Vehicle Course Control." Journal of Marine Science and Engineering 11, no. 10 (2023): 1904. http://dx.doi.org/10.3390/jmse11101904.

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A novel data-driven-based adaptive sliding-mode control scheme is proposed for unmanned surface vehicle course control in the presence of disturbances. The proposed method utilizes the model-free adaptive control (MFAC) theory. On account of the unknown dynamics of the USV course system, the control scheme is only established by online input and output information of the system. Based on a model-free adaptive control scheme, the system disturbance estimation technique is applied to compensate for the disturbances in the established compact form dynamic linearization data model. The controller
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Dissertations / Theses on the topic "Sliding model control"

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Parisi, Aaron Thomas. "An Application of Sliding Mode Control to Model-Based Reinforcement Learning." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/2054.

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The state-of-art model-free reinforcement learning algorithms can generate admissible controls for complicated systems with no prior knowledge of the system dynamics, so long as sufficient (oftentimes millions) of samples are available from the environ- ment. On the other hand, model-based reinforcement learning approaches seek to leverage known optimal or robust control to reinforcement learning tasks by mod- elling the system dynamics and applying well established control algorithms to the system model. Sliding-mode controllers are robust to system disturbance and modelling errors, and have
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Kandil, Mohamed Salah. "Sliding mode control of active magnetic bearings with low losses : a model-free approach." Thèse, Université de Sherbrooke, 2016. http://hdl.handle.net/11143/10166.

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Abstract : Over the past three decades, various fields have witnessed a successful application of active magnetic bearing (AMB) systems. Their favorable features include supporting high-speed rotation, low power consumption, and rotor dynamics control. Although their losses are much lower than roller bearings, these losses could limit the operation in some applications such as flywheel energy storage systems and vacuum applications. Many researchers focused their efforts on boosting magnetic bearings energy efficiency via minimizing currents supplied to electromagnetic coils either by a softwa
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Sanchez, Edinzo J. Iglesias. "Using fuzzy logic to enhance control performance of sliding mode control and dynamic matrix control." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001497.

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Wondimu, Nahom Abebe. "SIMULATED AND EXPERIMENTAL SLIDING MODE CONTROL OF A HYDRAULIC POSITIONING SYSTEM." University of Akron / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=akron1145419922.

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Fu, Lina. "Model-Based Extremum Seeking Control for a Class of Nonlinear Systems." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1290570109.

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Hasanaj, Edmir. "Experimental investigation of the boundary layer-based sliding mode control and single-input model-based sliding mode fuzzy logic control with applications to robot manipulators." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0019/MQ54109.pdf.

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Thome, De Faria Cassio. "Robust Model-Based Control of Nonlinear Systems for Bio-Inspired Autonomous Underwater Vehicles." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/23792.

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The growing need for ocean surveillance and exploration has pushed the development of novel autonomous underwater vehicle (AUV) technology. A current trend is to make use of bio-inspired propulsor to increase the overall system efficiency and performance, an improvement that has deep implications in the dynamics of the system. The goal of this dissertation is to propose a generic robust control framework specific for bio-inspired autonomous underwater vehicles (BIAUV). These vehicles utilize periodic oscillation of a flexible structural component to generate thrust, a propulsion mechanism that
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Al-Baidhani, Humam A. "Design and Implementation of Simplified Sliding-Mode Control of PWM DC-DC Converters for CCM." Wright State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1590930594283361.

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Alqahtani, Ayedh H. A. S. "Modeling and Control of Photovoltaic Systems for Microgrids." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1381786869.

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Costa, Giuseppe Electrical Engineering &amp Telecommunications Faculty of Engineering UNSW. "Robust Control For Gantry Cranes." Awarded by:University of New South Wales. Electrical Engineering and Telecommunications, 1999. http://handle.unsw.edu.au/1959.4/17609.

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In this thesis a class of robust non-linear controllers for a gantry crane system are discussed. The gantry crane has three degrees of freedom, all of which are interrelated. These are the horizontal traverse of the cart, the vertical motion of the goods (i.e. rope length) and the swing angle made by the goods during the movement of the cart. The objective is to control all three degrees of freedom. This means achieving setpoint control for the cart and the rope length and cancellation of the swing oscillations. A mathematical model of the gantry crane system is developed using Lagrangian dyn
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Books on the topic "Sliding model control"

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Palm, Rainer. Model Based Fuzzy Control: Fuzzy Gain Schedulers and Sliding Mode Fuzzy Controllers. Springer Berlin Heidelberg, 1997.

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Palm, Rainer. Model based fuzzy control: Fuzzy gain schedulers and sliding mode fuzzy controllers. Springer, 1997.

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Wilfrid, Perruquetti, and Barbot Jean Pierre 1958-, eds. Sliding mode control in engineering. M. Dekker, 2002.

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K, Spurgeon Sarah, ed. Sliding mode control: Theory and applications. Taylor & Francis, 1998.

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Utkin, Vadim I. Sliding Modes in Control and Optimization. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-84379-2.

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Utkin, Vadim I. Sliding Modes in Control and Optimization. Springer Berlin Heidelberg, 1992.

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Utkin, Vadim Ivanovich. Sliding mode control in electromechanical systems. Taylor & Francis, 1999.

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Bartoszewicz, Andrzej. Time-varying sliding modes for second and third order systems. Springer, 2009.

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Imine, Hocine. Sliding Mode Based Analysis and Identification of Vehicle Dynamics. Springer Berlin Heidelberg, 2011.

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Utkin, Vadim. Sliding mode control in electromechanical systems. Taylor & Frances, 1999.

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Book chapters on the topic "Sliding model control"

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Alwi, Halim, Christopher Edwards, and Chee Pin Tan. "Model-Reference Sliding Mode FTC." In Advances in Industrial Control. Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-650-4_10.

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Edgar N., Sanchez, Vega Carlos J., Suarez Oscar J., and Guanrong Chen. "Model-Based Sliding-Mode Control." In Nonlinear Pinning Control of Complex Dynamical Networks. CRC Press, 2021. http://dx.doi.org/10.1201/9781003181804-5.

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Palm, Rainer, Hans Hellendoorn, and Dimiter Driankov. "Model Based Design of Sliding Mode FLC." In Model Based Fuzzy Control. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-662-03401-9_3.

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Bouteraa, Yassine, and Ismail Ben Abdallah. "Estimated Model-Based Sliding Mode Controller for an Active Exoskeleton Robot." In Applications of Sliding Mode Control. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2374-3_10.

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Ghommam, Jawhar, and Faiçal Mnif. "Robust Adaptive Manoeuvering Control of an Autonomous Surface Vessel in the Presence of Ocean Currents and Parametric Model Uncertainty." In Applications of Sliding Mode Control. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2374-3_7.

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Xu, Qingsong, and Kok Kiong Tan. "Model Predictive Discrete-Time Sliding-Mode Control." In Advances in Industrial Control. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21623-2_4.

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Qian, Dianwei, and Jianqiang Yi. "Crane Mathematic Model." In Hierarchical Sliding Mode Control for Under-actuated Cranes. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48417-3_2.

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Han, Yaofei, Chao Gong, and Jinqiu Gao. "Observer-Based Robustness Improvement for FCS-MPCC Used in IMs." In Model Predictive Control for AC Motors. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8066-3_2.

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AbstractThis Chapter proposes a sliding mode (SM) disturbance observer based finite control set model predictive current control (FCS-MPCC) strategy to improve the control performance of induction motors. FCS-MPCC method is achieved based on the machine model, leading to the fact that the parameters have great impacts on the control performance, especially the steady-state characteristics.
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Tong, Shenghao, Long Zhao, Huaitao Shi, Zhiqiang Duo, and Cai He. "Multi-mode Sliding Mode Control of Four-Cable Parallel Robot Based on Wind Disturbance Observation." In Lecture Notes in Mechanical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1876-4_46.

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AbstractAiming at the problem of accurate trajectory tracking of four-cable parallel robot under wind disturbance in the process of material handling in buildings, a multi-mode sliding mode control (MSMC) method based on wind disturbance observer is proposed. Firstly, the wind field model is established, and the comprehensive wind speed model is introduced into the accurate dynamic model as a wind disturbance factor. Secondly, the wind disturbance observer is introduced to estimate the total disturbance of wind disturbance error in real time, which effectively reduces the switching gain, thus
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Corradini, Maria Letizia, Gianluca Ippoliti, Giuseppe Orlando, and Simone Terramani. "Study and Development of Robust Control Systems for Educational Drones." In Makers at School, Educational Robotics and Innovative Learning Environments. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77040-2_40.

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AbstractThis paper considers the problem of attitude and altitude control of quadrotors using the sliding mode control theory. The mathematical model of the quadrotor is derived using the Euler-Newton formalism. The sliding-mode is applied to the Parrot Mambo minidrone, which is a strong example of bringing educational robotics to formal (MATLAB, Python, JavaScript), non-formal (Tynker, Blockly, Swift Playground) and informal education. The control considered shows good performance and enhanced robustness.
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Conference papers on the topic "Sliding model control"

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Tao, Zhengtao, Xuejuan Shao, Laiqing Sun, Zhimei Chen, Jingang Zhang, and Zhicheng Zhao. "Model-Free Adaptive Sliding-Mode Control for Tower Cranes." In 2024 18th International Conference on Control, Automation, Robotics and Vision (ICARCV). IEEE, 2024. https://doi.org/10.1109/icarcv63323.2024.10821621.

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Li, Xing, and Zhengyang Zhu. "Discrete-Time Fixed-Step Sliding Mode Control Based Model-Free Adaptive Control." In 2025 IEEE 14th Data Driven Control and Learning Systems (DDCLS). IEEE, 2025. https://doi.org/10.1109/ddcls66240.2025.11065579.

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Wang, Chenqi, Yuan Li, and Yi Zhang. "Adaptive sliding mode preview control for SIRS model with saturation incidence." In 2024 43rd Chinese Control Conference (CCC). IEEE, 2024. http://dx.doi.org/10.23919/ccc63176.2024.10662188.

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Leśniewski, Piotr. "Reference model based sliding mode control of a platoon of vehicles." In 2024 28th International Conference on Methods and Models in Automation and Robotics (MMAR). IEEE, 2024. http://dx.doi.org/10.1109/mmar62187.2024.10680755.

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Dallabona, Alessio, Mogens Blanke, and Dimitrios Papageorgiou. "Model-free sliding mode control for hydraulic actuators under high load." In 2024 17th International Workshop on Variable Structure Systems (VSS). IEEE, 2024. http://dx.doi.org/10.1109/vss61690.2024.10753380.

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Lai, Yanchen, and Qiang fu. "Sliding mode and dual vector model predictive current control of PMSM." In Ninth International Conference on Energy System, Electricity and Power (ESEP 2024), edited by Mohan Lal Kolhe, Yunfei Mu, Ze Cheng, and Qian Xiao. SPIE, 2025. https://doi.org/10.1117/12.3060072.

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Wu, Xueqin, Fan Yu, and Yiyuan Shao. "Simplified Model and Sliding Mode Control Method of Active Power Filter." In 2025 International Conference on Power Electronics and Electric Drives (PEED). IEEE, 2025. https://doi.org/10.1109/peed63748.2025.00041.

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Li, Wei, Junqing Han, Shuai Fang, Yazhen Du, and Yang Cao. "Underactuated Ship Heading Control in Harbor Based on Model-Free Adaptive Sliding Mode Control." In 2024 4th International Conference on Industrial Automation, Robotics and Control Engineering (IARCE). IEEE, 2024. https://doi.org/10.1109/iarce64300.2024.00015.

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Crassidis, Agamemnon, and Raul Mittmann Reis. "Model-Free Sliding Mode Control Method." In International Conference of Control, Dynamic Systems, and Robotics. Avestia Publishing, 2016. http://dx.doi.org/10.11159/cdsr16.100.

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Qizhi Wang, Xiaoxia Wang, and Zhiren Cai. "Model reference based on sliding mode control." In 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/icicisys.2009.5358283.

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Reports on the topic "Sliding model control"

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Wells, Scott R. Sliding Mode Control Applied to Reconfigurable Flight Control Design. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada398917.

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Sagimori, Kenji, Mitsunobu Kajitani, Shinji Niwa, and Kenji Nakajima. Development of the EGR Control Using Sliding Mode Control. SAE International, 2005. http://dx.doi.org/10.4271/2005-08-0637.

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Verghese, George C., Benito Fernandez, and J. K. Hedrick. Stable, Robust Tracking by Sliding Mode Control,. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada188278.

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Emma, Olsson. Kolinlagring med biokol : Att nyttja biokol och hydrokol som kolsänka i östra Mellansverige. Linköping University Electronic Press, 2025. https://doi.org/10.3384/9789180759496.

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Pest inventory of a field is a way of knowing when the thresholds for pest control is reached. It is of increasing interest to use machine learning to automate this process, however, many challenges arise with detection of small insects both in traps and on plants. This thesis investigates the prospects of developing an automatic warning system for notifying a user of when certain pests are detected in a trap. For this, sliding window with histogram of oriented gradients based support vector machine were implemented. Trap detection with neural network models and a check size function were test
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