44,408 research outputs found

    Field Oriented Sliding Mode Control of Surface-Mounted Permanent Magnet AC Motors: Theory and Applications to Electrified Vehicles

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    Permanent magnet ac motors have been extensively utilized for adjustable-speed traction motor drives, due to their inherent advantages including higher power density, superior efficiency and reliability, more precise and rapid torque control, larger power factor, longer bearing, and insulation life-time. Without any proportional-and-integral (PI) controllers, this paper introduces novel first- and higher-order field-oriented sliding mode control schemes. Compared with the traditional PI-based vector control techniques, it is shown that the proposed field oriented sliding mode control methods improve the dynamic torque and speed response, and enhance the robustness to parameter variations, modeling uncertainties, and external load perturbations. While both first- and higher-order controllers display excellent performance, computer simulations show that the higher-order field-oriented sliding mode scheme offers better performance by reducing the chattering phenomenon, which is presented in the first-order scheme. The higher-order field-oriented sliding mode controller, based on the hierarchical use of supertwisting algorithm, is then implemented with a Texas Instruments TMS320F28335 DSP hardware platform to prototype the surface-mounted permanent magnet ac motor drive. Last, computer simulation studies demonstrate that the proposed field-oriented sliding mode control approach is able to effectively meet the speed and torque requirements of a heavy-duty electrified vehicle during the EPA urban driving schedule

    A Novel Higher-Order Sliding Mode Control Scheme for Uncertain Nonlinear Systems: Short-period Missile Control Application

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    The paper proposes a novel higher-order sliding modes (HOSM) control scheme for a class of uncertain nonlinear systems. The HOSM-based control scheme is developed based on the Filippo

    Predictive Second Order Sliding Control of Constrained Linear Systems with Application to Automotive Control Systems

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    This paper presents a new predictive second order sliding controller (PSSC) formulation for setpoint tracking of constrained linear systems. The PSSC scheme is developed by combining the concepts of model predictive control (MPC) and second order discrete sliding mode control. In order to guarantee the feasibility of the PSSC during setpoint changes, a virtual reference variable is added to the PSSC cost function to calculate the closest admissible set point. The states of the system are then driven asymptotically to this admissible setpoint by the control action of the PSSC. The performance of the proposed PSSC is evaluated for an advanced automotive engine case study, where a high fidelity physics-based model of a reactivity controlled compression ignition (RCCI) engine is utilized to serve as the virtual test-bed for the simulations. Considering the hard physical constraints on the RCCI engine states and control inputs, simultaneous tracking of engine load and optimal combustion phasing is a challenging objective to achieve. The simulation results of testing the proposed PSSC on the high fidelity RCCI model show that the developed predictive controller is able to track desired engine load and combustion phasing setpoints, with minimum steady state error, and no overshoot. Moreover, the simulation results confirm the robust tracking performance of the PSSC during transient operations, in the presence of engine cyclic variability.Comment: 6 pages, 5 figures, 2018 American Control Conferance (ACC), June 27-29, 2018, Milwaukee, WI, USA. [Accepted in Jan. 2018

    Robust and fast sliding-mode control for a DC-DC current-source parallel-resonant converter

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    Modern DC-DC resonant converters are normally built around a voltage-source series-resonant converter. This study aims to facilitate the practical use of current-source parallel-resonant converters due to their outstanding properties. To this end, this study presents a sliding-mode control scheme, which provides the following features to the closed-loop system: (i) high robustness to external disturbances and parameter variations and (ii) fast transient response during large and abrupt load changes. In addition, a design procedure for determining the values of the control parameters is presented. The theoretical contributions of this study are experimentally validated by selected tests on a laboratory prototype.Peer ReviewedPreprin

    Sliding mode control for robust and smooth reference tracking in robot visual servoing

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    [EN] An approach based on sliding mode is proposed in this work for reference tracking in robot visual servoing. In particular, 2 sliding mode controls are obtained depending on whether joint accelerations or joint jerks are considered as the discontinuous control action. Both sliding mode controls are extensively compared in a 3D-simulated environment with their equivalent well-known continuous controls, which can be found in the literature, to highlight their similarities and differences. The main advantages of the proposed method are smoothness, robustness, and low computational cost. The applicability and robustness of the proposed approach are substantiated by experimental results using a conventional 6R industrial manipulator (KUKA KR 6 R900 sixx [AGILUS]) for positioning and tracking tasks.Spanish Government, Grant/Award Number: BES-2010-038486; Generalitat Valenciana, Grant/Award Number: BEST/2017/029 and APOSTD/2016/044Muñoz-Benavent, P.; Gracia, L.; Solanes, JE.; Esparza, A.; Tornero, J. (2018). Sliding mode control for robust and smooth reference tracking in robot visual servoing. International Journal of Robust and Nonlinear Control. 28(5):1728-1756. https://doi.org/10.1002/rnc.3981S17281756285Hutchinson, S., Hager, G. D., & Corke, P. I. (1996). A tutorial on visual servo control. IEEE Transactions on Robotics and Automation, 12(5), 651-670. doi:10.1109/70.538972Chaumette, F., & Hutchinson, S. (2008). Visual Servoing and Visual Tracking. Springer Handbook of Robotics, 563-583. doi:10.1007/978-3-540-30301-5_25Corke, P. (2011). Robotics, Vision and Control. Springer Tracts in Advanced Robotics. doi:10.1007/978-3-642-20144-8RYAN, E. P., & CORLESS, M. (1984). Ultimate Boundedness and Asymptotic Stability of a Class of Uncertain Dynamical Systems via Continuous and Discontinuous Feedback Control. IMA Journal of Mathematical Control and Information, 1(3), 223-242. doi:10.1093/imamci/1.3.223Chaumette, F., & Hutchinson, S. (2006). Visual servo control. I. Basic approaches. IEEE Robotics & Automation Magazine, 13(4), 82-90. doi:10.1109/mra.2006.250573Chaumette, F., & Hutchinson, S. (2007). Visual servo control. II. Advanced approaches [Tutorial]. IEEE Robotics & Automation Magazine, 14(1), 109-118. doi:10.1109/mra.2007.339609Bonfe M Mainardi E Fantuzzi C Variable structure PID based visual servoing for robotic tracking and manipulation 2002 Lausanne, Switzerland https://doi.org/10.1109/IRDS.2002.1041421Solanes, J. E., Muñoz-Benavent, P., Girbés, V., Armesto, L., & Tornero, J. (2015). On improving robot image-based visual servoing based on dual-rate reference filtering control strategy. Robotica, 34(12), 2842-2859. doi:10.1017/s0263574715000454Elena M Cristiano M Damiano F Bonfe M Variable structure PID controller for cooperative eye-in-hand/eye-to-hand visual servoing 2003 Istanbul, Turkey https://doi.org/10.1109/CCA.2003.1223145Hashimoto, K., Ebine, T., & Kimura, H. (1996). Visual servoing with hand-eye manipulator-optimal control approach. IEEE Transactions on Robotics and Automation, 12(5), 766-774. doi:10.1109/70.538981Chan A Leonard S Croft EA Little JJ Collision-free visual servoing of an eye-in-hand manipulator via constraint-aware planning and control 2011 San Francisco, CA, USA https://doi.org/10.1109/ACC.2011.5991008Allibert, G., Courtial, E., & Chaumette, F. (2010). Visual Servoing via Nonlinear Predictive Control. Lecture Notes in Control and Information Sciences, 375-393. doi:10.1007/978-1-84996-089-2_20Kragic, D., & Christensen, H. I. (2003). Robust Visual Servoing. The International Journal of Robotics Research, 22(10-11), 923-939. doi:10.1177/027836490302210009Mezouar Y Chaumette F Path planning in image space for robust visual servoing 2000 San Francisco, CA, USA https://doi.org/10.1109/ROBOT.2000.846445Morel, G., Zanne, P., & Plestan, F. (2005). Robust visual servoing: bounding the task function tracking errors. IEEE Transactions on Control Systems Technology, 13(6), 998-1009. doi:10.1109/tcst.2005.857409Hammouda, L., Kaaniche, K., Mekki, H., & Chtourou, M. (2015). Robust visual servoing using global features based on random process. International Journal of Computational Vision and Robotics, 5(2), 138. doi:10.1504/ijcvr.2015.068803Yang YX Liu D Liu H Robot-self-learning visual servoing algorithm using neural networks 2002 Beijing, China https://doi.org/10.1109/ICMLC.2002.1174473Sadeghzadeh, M., Calvert, D., & Abdullah, H. A. (2014). Self-Learning Visual Servoing of Robot Manipulator Using Explanation-Based Fuzzy Neural Networks and Q-Learning. Journal of Intelligent & Robotic Systems, 78(1), 83-104. doi:10.1007/s10846-014-0151-5Lee AX Levine S Abbeel P Learning Visual Servoing With Deep Features and Fitted Q-Iteration 2017Fakhry, H. H., & Wilson, W. J. (1996). A modified resolved acceleration controller for position-based visual servoing. Mathematical and Computer Modelling, 24(5-6), 1-9. doi:10.1016/0895-7177(96)00112-4Keshmiri, M., Wen-Fang Xie, & Mohebbi, A. (2014). Augmented Image-Based Visual Servoing of a Manipulator Using Acceleration Command. IEEE Transactions on Industrial Electronics, 61(10), 5444-5452. doi:10.1109/tie.2014.2300048Edwards, C., & Spurgeon, S. (1998). Sliding Mode Control. doi:10.1201/9781498701822Zanne P Morel G Piestan F Robust vision based 3D trajectory tracking using sliding mode control 2000 San Francisco, CA, USAOliveira TR Peixoto AJ Leite AC Hsu L Sliding mode control of uncertain multivariable nonlinear systems applied to uncalibrated robotics visual servoing 2009 St. Louis, MO, USAOliveira, T. R., Leite, A. C., Peixoto, A. J., & Hsu, L. (2014). Overcoming Limitations of Uncalibrated Robotics Visual Servoing by means of Sliding Mode Control and Switching Monitoring Scheme. Asian Journal of Control, 16(3), 752-764. doi:10.1002/asjc.899Li, F., & Xie, H.-L. (2010). Sliding mode variable structure control for visual servoing system. International Journal of Automation and Computing, 7(3), 317-323. doi:10.1007/s11633-010-0509-5Kim J Kim D Choi S Won S Image-based visual servoing using sliding mode control 2006 Busan, South KoreaBurger W Dean-Leon E Cheng G Robust second order sliding mode control for 6D position based visual servoing with a redundant mobile manipulator 2015 Seoul, South KoreaBecerra, H. M., López-Nicolás, G., & Sagüés, C. (2011). A Sliding-Mode-Control Law for Mobile Robots Based on Epipolar Visual Servoing From Three Views. IEEE Transactions on Robotics, 27(1), 175-183. doi:10.1109/tro.2010.2091750Parsapour, M., & Taghirad, H. D. (2015). Kernel-based sliding mode control for visual servoing system. IET Computer Vision, 9(3), 309-320. doi:10.1049/iet-cvi.2013.0310Xin J Ran BJ Ma XM Robot visual sliding mode servoing using SIFT features 2016 Chengdu, ChinaZhao, Y. M., Lin, Y., Xi, F., Guo, S., & Ouyang, P. (2016). Switch-Based Sliding Mode Control for Position-Based Visual Servoing of Robotic Riveting System. Journal of Manufacturing Science and Engineering, 139(4). doi:10.1115/1.4034681Moosavian, S. A. A., & Papadopoulos, E. (2007). Modified transpose Jacobian control of robotic systems. Automatica, 43(7), 1226-1233. doi:10.1016/j.automatica.2006.12.029Sagara, S., & Taira, Y. (2008). Digital control of space robot manipulators with velocity type joint controller using transpose of generalized Jacobian matrix. Artificial Life and Robotics, 13(1), 355-358. doi:10.1007/s10015-008-0584-7Khalaji, A. K., & Moosavian, S. A. A. (2015). Modified transpose Jacobian control of a tractor-trailer wheeled robot. Journal of Mechanical Science and Technology, 29(9), 3961-3969. doi:10.1007/s12206-015-0841-3Utkin, V., Guldner, J., & Shi, J. (2017). Sliding Mode Control in Electro-Mechanical Systems. doi:10.1201/9781420065619Utkin, V. (2016). Discussion Aspects of High-Order Sliding Mode Control. IEEE Transactions on Automatic Control, 61(3), 829-833. doi:10.1109/tac.2015.2450571Romdhane, H., Dehri, K., & Nouri, A. S. (2016). Discrete second-order sliding mode control based on optimal sliding function vector for multivariable systems with input-output representation. International Journal of Robust and Nonlinear Control, 26(17), 3806-3830. doi:10.1002/rnc.3536Sharma, N. K., & Janardhanan, S. (2017). Optimal discrete higher-order sliding mode control of uncertain LTI systems with partial state information. International Journal of Robust and Nonlinear Control. doi:10.1002/rnc.3785LEVANT, A. (1993). Sliding order and sliding accuracy in sliding mode control. International Journal of Control, 58(6), 1247-1263. doi:10.1080/00207179308923053Levant, A. (2003). Higher-order sliding modes, differentiation and output-feedback control. International Journal of Control, 76(9-10), 924-941. doi:10.1080/0020717031000099029Bartolini, G., Ferrara, A., & Usai, E. (1998). Chattering avoidance by second-order sliding mode control. IEEE Transactions on Automatic Control, 43(2), 241-246. doi:10.1109/9.661074Siciliano, B., Sciavicco, L., Villani, L., & Oriolo, G. (2009). Robotics. Advanced Textbooks in Control and Signal Processing. doi:10.1007/978-1-84628-642-1Deo, A. S., & Walker, I. D. (1995). Overview of damped least-squares methods for inverse kinematics of robot manipulators. Journal of Intelligent & Robotic Systems, 14(1), 43-68. doi:10.1007/bf01254007WHEELER, G., SU, C.-Y., & STEPANENKO, Y. (1998). A Sliding Mode Controller with Improved Adaptation Laws for the Upper Bounds on the Norm of Uncertainties. Automatica, 34(12), 1657-1661. doi:10.1016/s0005-1098(98)80024-1Yu-Sheng Lu. (2009). Sliding-Mode Disturbance Observer With Switching-Gain Adaptation and Its Application to Optical Disk Drives. IEEE Transactions on Industrial Electronics, 56(9), 3743-3750. doi:10.1109/tie.2009.2025719Chen, X., Shen, W., Cao, Z., & Kapoor, A. (2014). A novel approach for state of charge estimation based on adaptive switching gain sliding mode observer in electric vehicles. Journal of Power Sources, 246, 667-678. doi:10.1016/j.jpowsour.2013.08.039Cong, B. L., Chen, Z., & Liu, X. D. (2012). On adaptive sliding mode control without switching gain overestimation. International Journal of Robust and Nonlinear Control, 24(3), 515-531. doi:10.1002/rnc.2902Taleb, M., Plestan, F., & Bououlid, B. (2014). An adaptive solution for robust control based on integral high-order sliding mode concept. International Journal of Robust and Nonlinear Control, 25(8), 1201-1213. doi:10.1002/rnc.3135Zhu, J., & Khayati, K. (2016). On a new adaptive sliding mode control for MIMO nonlinear systems with uncertainties of unknown bounds. International Journal of Robust and Nonlinear Control, 27(6), 942-962. doi:10.1002/rnc.3608Hafez AHA Cervera E Jawahar CV Hybrid visual servoing by boosting IBVS and PBVS 2008 Damascus, SyriaKermorgant O Chaumette F Combining IBVS and PBVS to ensure the visibility constraint 2011 San Francisco, CA, USACorke, P. I., & Hutchinson, S. A. (2001). A new partitioned approach to image-based visual servo control. IEEE Transactions on Robotics and Automation, 17(4), 507-515. doi:10.1109/70.954764Yang, Z., & Shen, S. (2017). Monocular Visual–Inertial State Estimation With Online Initialization and Camera–IMU Extrinsic Calibration. 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    A survey on fractional order control techniques for unmanned aerial and ground vehicles

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    In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

    Fast Adaptive Robust Differentiator Based Robust-Adaptive Control of Grid-Tied Inverters with a New L Filter Design Method

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    In this research, a new nonlinear and adaptive state feedback controller with a fast-adaptive robust differentiator is presented for grid-tied inverters. All parameters and external disturbances are taken as uncertain in the design of the proposed controller without the disadvantages of singularity and over-parameterization. A robust differentiator based on the second order sliding mode is also developed with a fast-adaptive structure to be able to consider the time derivative of the virtual control input. Unlike the conventional backstepping, the proposed differentiator overcomes the problem of explosion of complexity. In the closed-loop control system, the three phase source currents and direct current (DC) bus voltage are assumed to be available for feedback. Using the Lyapunov stability theory, it is proven that the overall control system has the global asymptotic stability. In addition, a new simple L filter design method based on the total harmonic distortion approach is also proposed. Simulations and experimental results show that the proposed controller assurances drive the tracking errors to zero with better performance, and it is robust against all uncertainties. Moreover, the proposed L filter design method matches the total harmonic distortion (THD) aim in the design with the experimental result
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