Simultaneous velocity, impact and force control

[EN] In this paper, we propose a control method to achieve three objectives simultaneously: velocity regulation during free motion, impact damping and finally force reference tracking. During impact, the parameters are switched in order to dissipate the energy of the system as fast as possible and the optimal switching criteria are deduced. The possibility of sliding regimes is analysed and the theoretical results are verified in simulations.We would like to thank the R&D&I Linguistic Assistance Office, Universidad Politecnica de Valencia (Spain), for Granting financial support for the linguistic revision of this paper. This work has been partially funded by the European project MASMICRO (Project number 500095-2), by the projects FEDER-CICYT with reference, DPI2005-08732C02-02 and DP12006-15320-C03-01, of the Ministry of Education and Science as well as by the research Project of the Generalitat Valenciana, GVPRE/2008 20080916.Zotovic Stanisic, R.; Valera Fernández, Á. (2009). Simultaneous velocity, impact and force control. Robotica. 27(7):1039-1048. https://doi.org/10.1017/S0263574709005451S1039104827710. Xu Y. , Hollerbach J. M. and Ma D. , “Force and Contact Transient Control Using Nonlinear PD Control,” Proceedings of the 1994 International Conference on Robotics and Automation (1994) pp. 924–930.Brach, R. M., & Goldsmith, W. (1991). Mechanical Impact Dynamics: Rigid Body Collisions. Journal of Engineering for Industry, 113(2), 248-249. doi:10.1115/1.2899694Chiaverini, S., & Sciavicco, L. (1993). The parallel approach to force/position control of robotic manipulators. IEEE Transactions on Robotics and Automation, 9(4), 361-373. doi:10.1109/70.246048Armstrong, B. S. R., Gutierrez, J. A., Wade, B. A., & Joseph, R. (2006). Stability of Phase-Based Gain Modulation with Designer-Chosen Switch Functions. The International Journal of Robotics Research, 25(8), 781-796. doi:10.1177/0278364906067543Volpe, R., & Khosla, P. (1993). A Theoretical and Experimental Investigation of Impact Control for Manipulators. The International Journal of Robotics Research, 12(4), 351-365. doi:10.1177/027836499301200403Impact modeling and control for industrial manipulators. (1998). IEEE Control Systems, 18(4), 65-71. doi:10.1109/37.710879Brogliato, B., Niculescu, S.-I., & Orhant, P. (1997). On the control of finite-dimensional mechanical systems with unilateral constraints. IEEE Transactions on Automatic Control, 42(2), 200-215. doi:10.1109/9.554400Brogliato, B. (1999). Nonsmooth Mechanics. Communications and Control Engineering. doi:10.1007/978-1-4471-0557-2Armstrong, B., & Wade, B. A. (2000). Nonlinear PID Control with Partial State Knowledge: Damping without Derivatives. The International Journal of Robotics Research, 19(8), 715-731. doi:10.1177/02783640022067120Controlling contact transition. (1994). IEEE Control Systems, 14(1), 25-30. doi:10.1109/37.257891Seraji, H. (1998). Nonlinear and Adaptive Control of Force and Compliance in Manipulators. The International Journal of Robotics Research, 17(5), 467-484. doi:10.1177/027836499801700501Volpe, R., & Khosla, P. (1993). A theoretical and experimental investigation of explicit force control strategies for manipulators. IEEE Transactions on Automatic Control, 38(11), 1634-1650. doi:10.1109/9.262033A nonlinear PD controller for force and contact transient control. (1995). IEEE Control Systems, 15(1), 15-21. doi:10.1109/37.341859Seraji, H., & Colbaugh, R. (1997). Force Tracking in Impedance Control. The International Journal of Robotics Research, 16(1), 97-117. doi:10.1177/027836499701600107Armstrong, B., Neevel, D., & Kusik, T. (2001). New results in NPID control: Tracking, integral control, friction compensation and experimental results. IEEE Transactions on Control Systems Technology, 9(2), 399-406. doi:10.1109/87.91139

Time Variant Predictive Control of Autonomous Vehicles: Time Variant Predictive Control of Autonomous Vehicles

This paper develops a linearized time variant model predictive control (MPC) approach for controlling autonomous vehicle tracking on feasible trajectories generated from the vehicle nonlinear ordinary differential equations (ODEs). The paper is an application of the results from computational schemes for nonlinear model predictive control published in (International Journal of Control, Automation and Systems 2011 9(5), 958-965; Mechatronics 2013, Trajectory Generation for Autonomous Vehicles, 615-626, Springer). The vehicle nonlinear dynamic equations are derived and solved in MPC optimizer. Solution for the closed loop control is obtained by solving online the vehicle dynamic ODEs. Simulations for the new schemes are presented and analyse

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

[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. 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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). 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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). 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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. 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(2005). ViSP for visual servoing: a generic software platform with a wide class of robot control skills. IEEE Robotics & Automation Magazine, 12(4), 40-52. doi:10.1109/mra.2005.157702