Modeling and compensation control of asymmetric hysteresis in a pneumatic artificial muscle

Pneumatic artificial muscle is a novel compliance actuator, and it has many excellent actuator characteristics, such as high power density, safety, and compliance. However, it also has strong nonlinear and asymmetric hysteresis, which makes the accurate trajectory control for a pneumatic artificial muscle very difficult. In this article, the pressure/length hysteresis of a pneumatic artificial muscle was analyzed via an isotonic test. And then, it was described using extended unparallel Prandtl–Ishlinskii model, and the model parameters were identified by an adaptive weight particle swarm optimization with a mutation portion algorithm. For the comparison, the classical Prandtl–Ishlinskii was also considered, and its parameters were identified by least square method. Based on the hysteresis model built by extended unparallel Prandtl–Ishlinskii model, an integral inverse compensator was proposed, and then a proportional–integral–derivative controller with the integral inverse compensator (integral inverse-proportional–integral–derivative) was designed. The simulations and experiments validated that the integral inverse-proportional–integral–derivative controller has good dynamic performance. Compared with conventional proportional–integral–derivative controller without a hysteresis compensator, the control precision of integral inverse-proportional–integral–derivative controller is improved by 43.86%.

[1]  Bertrand Tondu,et al.  Modelling of the McKibben artificial muscle: A review , 2012 .

[2]  Saeid Bashash,et al.  A Polynomial-Based Linear Mapping Strategy for Feedforward Compensation of Hysteresis in Piezoelectric Actuators , 2008 .

[3]  Gabriella Eula,et al.  Soft Pneumatic Actuators for Rehabilitation , 2014 .

[4]  Jian Huang,et al.  Nonlinear Disturbance Observer-Based Dynamic Surface Control for Trajectory Tracking of Pneumatic Muscle System , 2014, IEEE Transactions on Control Systems Technology.

[5]  P.D. Dimitropoulos,et al.  A 3-D hybrid Jiles-Atherton/Stoner-Wohlfarth magnetic hysteresis model for inductive sensors and actuators , 2006, IEEE Sensors Journal.

[6]  Thanh Nho Do,et al.  A survey on hysteresis modeling, identification and control , 2014 .

[7]  Chih-Jer Lin,et al.  Hysteresis modeling and tracking control for a dual pneumatic artificial muscle system using Prandtl–Ishlinskii model , 2015 .

[8]  T. Tjahjowidodo,et al.  A New Approach to Modeling Hysteresis in a Pneumatic Artificial Muscle Using The Maxwell-Slip Model , 2011, IEEE/ASME Transactions on Mechatronics.

[9]  Darwin G. Caldwell,et al.  Braided Pneumatic Muscle Actuators , 1993 .

[10]  Bo Song,et al.  Compensating asymmetric hysteresis for nanorobot motion control , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[11]  Tianyou Chai,et al.  Compensation of Hysteresis Nonlinearity in Magnetostrictive Actuators With Inverse Multiplicative Structure for Preisach Model , 2014, IEEE Transactions on Automation Science and Engineering.

[12]  Tang Zhi-hong.  Mechanism Design and Realization of Joint of Pneumatic Muscle of Manipulator , 2009 .

[13]  Harald Aschemann,et al.  Comparison of Model-Based Approaches to the Compensation of Hysteresis in the Force Characteristic of Pneumatic Muscles , 2014, IEEE Transactions on Industrial Electronics.

[14]  Takahiro Kosaki,et al.  Control of a Parallel Manipulator Driven by Pneumatic Muscle Actuators Based on a Hysteresis Model , 2011 .

[15]  Livija Cveticanin,et al.  Dynamic modeling of a pneumatic muscle actuator with two-direction motion , 2015 .

[16]  K. Kuhnen,et al.  Inverse feedforward controller for complex hysteretic nonlinearities in smart-material systems , 2001 .

[17]  Lining Sun,et al.  Improving positioning accuracy of piezoelectric actuators by feedforward hysteresis compensation based on a new mathematical model , 2005 .

[18]  Howard A. Baldwin.  Realizable Models of Muscle Function , 1969 .

[19]  Klaus Kuhnen,et al.  Modeling, Identification and Compensation of Complex Hysteretic Nonlinearities: A Modified Prandtl - Ishlinskii Approach , 2003, Eur. J. Control.

[20]  Xiaobo Tan,et al.  Modeling and inverse compensation of hysteresis in vanadium dioxide using an extended generalized Prandtl-Ishlinskii model , 2014 .

[21]  Christopher D. Rahn,et al.  Model-Based Shape Estimation for Soft Robotic Manipulators: The Planar Case , 2014 .

[22]  George Nikolakopoulos,et al.  Piecewise Affine Modeling and Constrained Optimal Control for a Pneumatic Artificial Muscle , 2014, IEEE Transactions on Industrial Electronics.

[23]  Chun-Yi Su,et al.  A note on the properties of a generalized Prandtl–Ishlinskii model , 2011 .

[24]  Armen Der Kiureghian,et al.  Generalized Bouc-Wen model for highly asymmetric hysteresis , 2006 .

[25]  Radhika Nagpal,et al.  Design and control of a bio-inspired soft wearable robotic device for ankle–foot rehabilitation , 2014, Bioinspiration & biomimetics.

[26]  Tegoeh Tjahjowidodo,et al.  A new approach of friction model for tendon-sheath actuated surgical systems: Nonlinear modelling and parameter identification , 2015 .

[27]  Yuansheng Chen,et al.  A modified prandtl-ishlinskii model for modeling asymmetric hysteresis of piezoelectric actuators , 2010, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[28]  Conor J. Walsh,et al.  Actuators: A Bioinspired Soft Actuated Material (Adv. Mater. 8/2014) , 2014 .

[29]  Limin Zhu,et al.  Real-time inverse hysteresis compensation of piezoelectric actuators with a modified Prandtl-Ishlinskii model. , 2012, The Review of scientific instruments.