Academic literature on the topic 'Backstepping-based control'
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Journal articles on the topic "Backstepping-based control"
Benaskeur, A. R., and A. Desbiens. "Backstepping-based adaptive PID control." IEE Proceedings - Control Theory and Applications 149, no. 1 (January 1, 2002): 54–59. http://dx.doi.org/10.1049/ip-cta:20020100.
Full textTran, Thanh T., and Oscar R. Gonzalez. "Backstepping-based control methodology for aircraft roll dynamics." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 234, no. 4 (July 3, 2019): 566–74. http://dx.doi.org/10.1177/0959651819860294.
Full textBurlion, L., T. Ahmed-Ali, and N. Seube. "Glider's roll control based on backstepping." IFAC Proceedings Volumes 37, no. 10 (July 2004): 161–65. http://dx.doi.org/10.1016/s1474-6670(17)31725-1.
Full textSu, Qingyu, Fei Dong, and Xueqiang Shen. "Improved Adaptive Backstepping Sliding Mode Control of Static Var Compensator." Energies 11, no. 10 (October 14, 2018): 2750. http://dx.doi.org/10.3390/en11102750.
Full textLi, Mei Hong, Jian Yin, Xue Yang Sun, Jin Xiang Xu, and Mei Mei Zhang. "Design of Missile Longitudinal Control System Based on Backstepping Control." Applied Mechanics and Materials 496-500 (January 2014): 1401–6. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.1401.
Full textShen, Dong Kai, Jing Jing Wang, and Zheng Hua Liu. "Robust BackStepping Control Based DRNN for Flight Simulator." Advanced Materials Research 139-141 (October 2010): 1708–13. http://dx.doi.org/10.4028/www.scientific.net/amr.139-141.1708.
Full textKulkarni, A., and A. Kumar. "Backstepping-based adaptive control for underactuated systems." International Journal of System Control and Information Processing 1, no. 4 (2015): 340. http://dx.doi.org/10.1504/ijscip.2015.075878.
Full textKristiansen, R., P. J. Nicklasson, and J. T. Gravdahl. "Satellite Attitude Control by Quaternion-Based Backstepping." IEEE Transactions on Control Systems Technology 17, no. 1 (January 2009): 227–32. http://dx.doi.org/10.1109/tcst.2008.924576.
Full textFalkena, W., C. Borst, E. R. van Oort, and Q. P. Chu. "Sensor-Based Backstepping." Journal of Guidance, Control, and Dynamics 36, no. 2 (March 2013): 606–10. http://dx.doi.org/10.2514/1.56581.
Full textKim, Yeonsoo, Tae Hoon Oh, Taekyoon Park, and Jong Min Lee. "Backstepping control integrated with Lyapunov-based model predictive control." Journal of Process Control 73 (January 2019): 137–46. http://dx.doi.org/10.1016/j.jprocont.2018.12.007.
Full textDissertations / Theses on the topic "Backstepping-based control"
Riccardo, Zanella Riccardo. "Decoupled Controllers for Mobile Manipulation with Aerial Robots : Design, Implementation and Test." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187649.
Full textRedaud, Jeanne. "Robust control of linear hyperbolic partial differential equations systems interconnected in a chain." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPAST153.
Full textThis thesis focuses on designing robust output-feedback backstepping-based controllers for hyperbolic partial differential equation (PDE) systems interconnected in a chain structure. We take advantage of connections between the class of hyperbolic PDE systems under consideration and time-delay systems of the neutral type presented in Part I. Then, we focus on two classes of chain structures. First, we consider the case where the actuation is available at one end (Part II) for two different networks (ODE-PDE-ODE and arbitrarily many N PDEs-ODE). Such chain structures can be found in drilling applications. Next, we consider a simple chain of two hyperbolic PDE subsystems where the actuation is available at the junction (Part III). A more general integral transform is necessary for its stabilization. Finally, we explore controller design tuning and implementation limitations of backstepping-based controllers (Part IV). We question the choice of a reachable target system with specific stability properties. Additionally, we examine the potential of machine learning techniques to improve computation time in distributed state and parameter estimation
Sadelli, Lounis. "Modélisation, observation et commande de robots vasculaires magnétiques." Thesis, Orléans, 2016. http://www.theses.fr/2016ORLE2065/document.
Full textMinimally invasive surgery is an active research area since such systems have the potential to perform complex surgical procedures such as targeted therapies or in situ diagnosis, while minimizing trauma, side effects and recovery time. Miniaturized systems magnetically propelled by remote actuation can achieve swimming through the blood vessels network in order to provide targeted therapy, even for hard-to-reach human organs. This PhD thesis aims at addressing i) a review on the modeling of microrobots immersed in blood vessels, ii) a classification of the state space forms of such systems, iii) the synthesis of state feedbacks ensuring the stabilization of the microrobots along a reference trajectory, iv) the synthesis of observers to rebuild the unmeasured state variables. Magnetic microrobots swimming in a blood vessel face the hydrodynamic drag, surfacic and contact forces, magnetic interactions, and their apparent weight. These untethered robots are actuated by magnetic fields or magnetic gradients generation, and their localization is ensured by a medical imager. The microrobots dynamics (the so-called reduced system) lead to a nonlinear affine control subsystem with drift, and exhibits many uncertain physiological parameters, such as the blood velocity which can hardly be measured. The blood flow dynamics (the so-called fluidic system) are then modeled as an autonomous subsystem. These two subsystems result in an extended system describing the whole (robot and fluid) dynamics. The control objective is to stabilize the state of the reduced system along a reference trajectory, which is performed by an adaptive backstepping synthesis. Yet the full state is not accessible. We then synthesize either MVT or immersion based observers for the extended system, when the blood pulsation is either known or not. The output feedback stability is then proved. The stability and robustness to output noise, parametric uncertainty, and modeling errors are then illustrated by simulations
Wang, Yu-Long, and 王裕龍. "Adaptive Backstepping Control Based On Bond Graph." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/41118269880498414414.
Full text國立清華大學
動力機械工程學系
89
In most adaptive backstepping control applications, systems are expressed in sets of equations and mathematical control theory is applied. Such an approach frequently loses the physical aspect of system properties and control performance. In this paper, by using bond graphs to analyze the energy interaction among subsystems, systematic procedures are developed to characterize the closed-loop system behavior from the open-loop bond-graph model. The results presented facilitate separation of design issues from realization issues through high-level abstraction, and establish a clear connection between model uncertainties and controller complexity.
Chang, Chih-Kai, and 張智凱. "FPGA-Based Adaptive Backstepping Control for Linear Induction Motor Drive." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/93389512897072685020.
Full text國立東華大學
電機工程學系
94
An FPGA-based adaptive backstepping controller, which combines both the merits of adaptive law and backstepping control, is proposed in this thesis to control the mover position of a linear induction motor (LIM) drive to compensate the uncertainties including the friction force. First, the dynamic model of an indirect field-oriented LIM drive is derived. Next, an FPGA-based LIM drive system, which consists of FPGA development board, D/A converters, a ramp comparison current-controlled PWM, and IGBT inverter, is implemented. Then, a proportional-intergral-derivative (PID) computed-torque controller is designed, but the tracking response is not good. Moreover, a backstepping controller and a backstepping sliding-mode controller are presented. The uncertainties are lumped and the upper bound of the lumped uncertainty is necessary in the design of the backstepping controller and the backstepping sliding-mode controller. However, the upper bound of the lumped uncertainty is difficult to obtain in advance in practical applications. Therefore, an adaptive law is derived to adapt the value of the lumped uncertainty in real time, and an adaptive backstepping controller and an adaptive backstepping sliding-mode controller are designed to make the LIM drive possessing the advantages of good transient control performance and robustness. Finally, one can verify that the adaptive backstepping control systems are better than the conventional backstepping control systems from the experimental tracking responses.
Kao, Hui-Hsiang, and 高暉翔. "Wavelet-based Adaptive Backstepping Control for Uncertain Systems with Actuator Saturation." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/90372809582777520267.
Full text國立臺灣師範大學
應用電子科技研究所
98
Three control methods for nonlinear systems are proposed in this study. The first controller design is about a wavelet adaptive backstepping controller for affine nonlinear systems. The controller is comprised of a wavelet identifier and actuator saturation. The second controller design is about a wavelet adaptive backstepping controller for nonaffine nonlinear systems. A wavelet adaptive backstepping controller for a nonaffine system is proposed in this paper. The control scheme combines the backstepping technique and adaptive control with wavelet function. The wavelet function has well performance. It is much proper to online compute the system dynamics by tuning its interior parameters. A mean-value estimation method is also proposed to avoid a higher-order derivative problem generated by Taylor linearization expansion.The third controller design is about a wavelet adaptive backstepping controller for nonaffine nonlinear systems with first order filters. Furthermore, the stability of the system with the mean-value theorem is dissected through Lyapunov functions. In the end, simulation results illustrate the application of the proposed scheme.
Weng, Ming-Hong, and 翁銘鴻. "FPGA-Based Adaptive Backstepping Fuzzy Control for aMicro-positioning Scott-Russell Mechanism." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/37377151779742800006.
Full text國立高雄第一科技大學
系統與控制工程研究所
95
This paper utilizes the Field Programmable Gate Array (FPGA) and Nios II embedded processor technologies to design a controller IC for a micro-positioning Scott-Russell (SR) mechanism, which is driven by a piezoelectric actuator (PA). The analog to digital (A/D) and digital to analog (D/A) conversion circuits are important role to achieved the communicated objective with the FPGA. In system identification, the main objective is to identify the hysteresis effect of the piezoelectric element (PE), and shows its influence on the dynamic responses of the SR mechanism. The identification method based on real-coded genetic algorithm (RGA) has the advantages to identify the parameters of the SR mechanism and the Bouc-Wen hysteresis model simultaneously. For the controller design, the adaptive backstepping fuzzy control (ABFC) method is developed to achieve the motion control and the fuzzy logic method (FLM) is utilized to find the best adaptation gain of the adaptation law and control gain of the stabilization controls. This ABFC controller method can improve the transient and asymptotic tracking performances, and make the SR mechanism keep good working performance when external disturbances exist in the control system. Finally, we successfully apply the system-on-a-programmable-chip (SoPC) technologies to develop the motion controller IC, and achieve the advantages of reduce space, high performance and low cost.
Wang, Chao-Min, and 王超民. "Backstepping Based Hybrid Adaptive Control of Robot Manipulators Driven by Induction Motors." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/17898845881755446849.
Full text國立交通大學
電機與控制工程系
87
In this thesis, we have made plainly delineation for the proposed nonlinear voltage input controller for robot manipulators driven by induction motors in the existent literature. And follow the same design procedure, simulated and experimental result is then presented to illustrate the position tracking performance for the proposed controller and system stability. Specially, we make complete representation for how to setup the experimental hardware. Owing to the nonlinear controller is designed under the assumption that exact model knowledge is known, say, without considering the effect of system model parametric uncertainties. Then, we focused on the mechanical subsystem parametric uncertainties and proposed novel rotor flux and stator current observer to derive the adaptive, partial-state feedback, position tracking controller to compensate the degraded performance caused by without considering the system model parametric uncertainties. Through the use of systematic design approach backstepping and nonlinear damping to guarantee boundedness of trajectories even when no upper bound on the uncertainties is known. Under the mechanical subsystem parametric uncertainties, the proposed voltage input controller only requires measurements of link position and stator winding currents. Finally, we conclude a theorem to insure the controller stability and simulation results are presented to illustrate the link position tracking error, and rotor flux and stator current estimated error are asymptotically stable.
Lee, Hou-Ze, and 李後澤. "Position Control System of Linear Pluse Motor Based on Robust Backstepping Approach." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/397739.
Full text國立虎尾科技大學
電機工程研究所
100
This thesis is based on the principle of robust backstepping control to develop a position-servo control system for linear pulse motor (LPM). To explore a high performance servo control technology, the complete theory is formulated via systematic analysis and synthesis process. The dynamic model is first established by using the concept of coordinate transformation that transfers the mathematic model of LPM into a compact form for facility of designing work. Then, considering the effects of load disturbance and parameter variation, the proposed approach employs the advantages of fuzzy neural network and adaptive tuning technique to the development of robust backstepping control algorithm. Various motion trajectories are utilized to examine the performance of the control system. Simulation and experiment results demonstrate the accuracy, validity, and highly robust ability of the proposed system.
Wood, Rohin. "Lyapunov-based control strategies for the global control of symmetric VTOL UAVs." Thesis, 2007. http://hdl.handle.net/2440/59390.
Full textThesis (Ph.D.) -- University of Adelaide, School of Mechanical Engineering, 2007
Book chapters on the topic "Backstepping-based control"
Stauter, Peter, Hubert Gattringer, Wolfgang Höbart, and Hartmut Bremer. "Passivity Based Backstepping Control of an Elastic Robot." In ROMANSY 18 Robot Design, Dynamics and Control, 315–22. Vienna: Springer Vienna, 2010. http://dx.doi.org/10.1007/978-3-7091-0277-0_37.
Full textMeng, Fanfeng, Lin Zhao, and Jinpeng Yu. "Backstepping Based Neuroadaptive Control for Uncertain Robot Systems." In Proceedings of 2018 Chinese Intelligent Systems Conference, 889–96. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2288-4_83.
Full textJiaqi, Liu, Chen Bailin, Yang Wenlong, Shi Zhongjiao, and Wang Wei. "Tracking Differentiation Guidance Law Based on Backstepping Control." In Lecture Notes in Electrical Engineering, 5054–62. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6613-2_488.
Full textTorres, M., and R. Ortega. "Feedback Linearization, Integrator Backstepping and Passivity-Based Controller Designs: A Comparison Example." In Perspectives in Control, 97–115. London: Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-1276-1_8.
Full textChen, Penghao, Tianping Zhang, Houbin Qian, and Yang Yi. "Backstepping-Based Adaptive Neural Control of Constrained Nonlinear Systems." In Lecture Notes in Electrical Engineering, 145–54. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8450-3_16.
Full textDalwadi, Nihal, Dipankar Deb, and Stepan Ozana. "Nonlinear Disturbance Observer-Based Backstepping Control of Tail-Sitter Quadrotors." In Studies in Systems, Decision and Control, 19–42. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9744-0_2.
Full textWang, Chenglong, Jianzhen Chen, Junjie Qiu, and WenBin Ma. "Anti-Jamming Control of Quadcopter Based on Backstepping Sliding Mode Control Algorithm." In Lecture Notes in Electrical Engineering, 195–208. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9243-0_21.
Full textZhang, Chuang, and Chen Guo. "Stabilization of Underactuated Surface Vessel Based on Backstepping Control Method." In Proceedings of the 2015 Chinese Intelligent Automation Conference, 117–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46463-2_14.
Full textWang, Lijun, Jiaxuan Yan, Tianyu Cao, and Ningxi Liu. "Manipulator Control Law Design Based on Backstepping and ADRC Methods." In Lecture Notes in Electrical Engineering, 261–69. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8450-3_28.
Full textKabba, Abdelaziz, Hassan El Fadil, Abdellah Lassioui, Zakariae El Idrissi, Soukaina Nady, Yassine Ait Jillali, and Halima Housny. "Backstepping-Based Control of a PV Inverter in Islanded Mode." In Lecture Notes in Electrical Engineering, 506–18. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0126-1_45.
Full textConference papers on the topic "Backstepping-based control"
Cong, Binglong, Xiangdong Liu, and Zhen Chen. "Backstepping based adaptive sliding mode control for spacecraft attitude maneuvers." In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334777.
Full textNazir, Saqib, Nouman Ashraf, and Iftikhar Ahmad. "Backstepping based control of heave-induced pressure deviations in managed pressure drilling." In 2016 UKACC 11th International Conference on Control (CONTROL). IEEE, 2016. http://dx.doi.org/10.1109/control.2016.7737518.
Full textWu Sai and Deng Feiqi. "Congestion control based on backstepping approach." In 2008 Chinese Control Conference (CCC). IEEE, 2008. http://dx.doi.org/10.1109/chicc.2008.4605393.
Full textRanger, P., and A. Desbiens. "Improved backstepping-based adaptive PID control." In 4th International Conference on Control and Automation. Final Program and Book of Abstracts. IEEE, 2003. http://dx.doi.org/10.1109/icca.2003.1594997.
Full textChou, Fang-Chieh, Shu-Xia Tang, Xiao-Yun Lu, and Alexandre Bayen. "Backstepping-Based Time-Gap Regulation for Platoons." In 2019 American Control Conference (ACC). IEEE, 2019. http://dx.doi.org/10.23919/acc.2019.8814914.
Full textJingjing, Huang, Zhang Aimin, Sun Yuangang, Zhang Hang, Zhang Chao, and Ren Zhigang. "Backstepping based direct power control for rectifier." In 2014 26th Chinese Control And Decision Conference (CCDC). IEEE, 2014. http://dx.doi.org/10.1109/ccdc.2014.6852712.
Full textXiaohai Li, Jizong Xiao, and Zijun Cai. "Backstepping based multiple mobile robots formation control." In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2005. http://dx.doi.org/10.1109/iros.2005.1545161.
Full textTian, Congling, Jingwen Wang, Zhaojie Yin, and Guohui Yu. "Integral backstepping based nonlinear control for quadrotor." In 2016 35th Chinese Control Conference (CCC). IEEE, 2016. http://dx.doi.org/10.1109/chicc.2016.7555034.
Full textJin Young Choi and J. Farrell. "Observer-based backstepping control using online approximation." In Proceedings of 2000 American Control Conference (ACC 2000). IEEE, 2000. http://dx.doi.org/10.1109/acc.2000.879250.
Full textShi, Ke, Zuo Wang, Chao Wu, and Shihua Li. "GPIO based backstepping control for electronic throttle." In IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2017. http://dx.doi.org/10.1109/iecon.2017.8217057.
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