PID Position Control of McKibben Pneumatic Artificial Muscle Using Only Pressure Feedback
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[1] George Nikolakopoulos,et al. Piecewise Affine Modeling and Constrained Optimal Control for a Pneumatic Artificial Muscle , 2014, IEEE Transactions on Industrial Electronics.
[2] Toshiro Noritsugu,et al. Application of rubber artificial muscle manipulator as a rehabilitation robot , 1996, Proceedings 5th IEEE International Workshop on Robot and Human Communication. RO-MAN'96 TSUKUBA.
[3] H.F. Durrant-Whyte,et al. A new approach for filtering nonlinear systems , 1995, Proceedings of 1995 American Control Conference - ACC'95.
[4] M. Yamakita,et al. Comparative study of simultaneous parameter-state estimations , 2004, Proceedings of the 2004 IEEE International Conference on Control Applications, 2004..
[5] G.S. Sawicki,et al. Powered lower limb orthoses: applications in motor adaptation and rehabilitation , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..
[6] Manukid Parnichkun,et al. Position control of a pneumatic surgical robot using PSO based 2-DOF H∞ loop shaping structured controller , 2017 .
[7] Oussama Khatib,et al. A hybrid actuation approach for human-friendly robot design , 2008, 2008 IEEE International Conference on Robotics and Automation.
[8] Daniel W. Repperger,et al. Controller design involving gain scheduling for a large scale pneumatic muscle actuator , 1999, Proceedings of the 1999 IEEE International Conference on Control Applications (Cat. No.99CH36328).
[9] Kiminao Kogiso,et al. Applications of UKF and EnKF to estimation of contraction ratio of McKibben pneumatic artificial muscles , 2017, 2017 American Control Conference (ACC).
[10] Daisuke Sasaki,et al. Wearable Master-Slave Training Device for Lower Limb Constructed with Pneumatic Rubber Artificial Muscles , 2008, J. Robotics Mechatronics.
[11] Darwin G. Caldwell,et al. Adaptive position control of antagonistic pneumatic muscle actuators , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.
[12] Takamitsu Matsubara,et al. Pneumatic artificial muscle-driven robot control using local update reinforcement learning , 2017, Adv. Robotics.
[13] Hongjiu Yang,et al. Angle tracking of a pneumatic muscle actuator mechanism under varying load conditions , 2017 .
[14] Francesco Amato,et al. Identification and modelling of the friction-induced hysteresis in pneumatic actuators for biomimetic robots , 2014, 22nd Mediterranean Conference on Control and Automation.
[15] George Nikolakopoulos,et al. Adaptive Internal Model Control scheme for a Pneumatic Artificial Muscle , 2013, 2013 European Control Conference (ECC).
[16] Marc D. Killpack,et al. Control of a pneumatically actuated, fully inflatable, fabric-based, humanoid robot , 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).
[17] Scott Pardoel,et al. Dynamic contraction behaviour of pneumatic artificial muscle , 2017 .
[18] A. L. Morales,et al. Dynamic behaviour of pneumatic linear actuators , 2017 .
[19] Jun Ueda,et al. An Asymptotically Stable Pressure Observer Based on Load and Displacement Sensing for Pneumatic Actuators With Long Transmission Lines , 2017, IEEE/ASME Transactions on Mechatronics.
[20] Kiminao Kogiso,et al. Hybrid nonlinear model of McKibben pneumatic artificial muscle systems incorporating a pressure-dependent Coulomb friction coefficient , 2015, 2015 IEEE Conference on Control Applications (CCA).
[21] Kiminao Kogiso,et al. Hybrid modeling of McKibben pneumatic artificial muscle systems , 2011, 2011 IEEE International Conference on Industrial Technology.
[22] Daniel W. Repperger,et al. Fuzzy PD+I learning control for a pneumatic muscle , 2003, The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03..
[23] Kiminao Kogiso,et al. Efficient PSO-based algorithm for parameter estimation of McKibben PAM model , 2017, 2017 IEEE Conference on Control Technology and Applications (CCTA).
[24] J. Landaluze,et al. Modelling in Modelica and position control of a 1-DoF set-up powered by pneumatic muscles , 2010 .
[25] Jun Morimoto,et al. Optimal control approach for pneumatic artificial muscle with using pressure-force conversion model , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[26] Takamitsu Matsubara,et al. Kernel dynamic policy programming: Practical reinforcement learning for high-dimensional robots , 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).
[27] Henrique Marra Menegaz,et al. A Systematization of the Unscented Kalman Filter Theory , 2015, IEEE Transactions on Automatic Control.
[28] Osamu Kaneko,et al. Data-driven tuning of nonlinear internal model controllers for pneumatic artificial muscles , 2014, 2014 4th Australian Control Conference (AUCC).
[29] B. Tondu,et al. Closed-loop position control of artificial muscles with a single integral action: Application to robust positioning of McKibben artificial muscle , 2013, 2013 IEEE International Conference on Mechatronics (ICM).
[30] Hendrik Van Brussel,et al. Cascade position control of a single pneumatic artificial muscle-mass system with hysteresis compensation , 2010 .