Planar positioning systems are widely utilized in micro and nano applications.The challenges in modeling and control of XYΘflexure-based mechanisms include hysteresis of the piezoelectric actuators,couplings among th...Planar positioning systems are widely utilized in micro and nano applications.The challenges in modeling and control of XYΘflexure-based mechanisms include hysteresis of the piezoelectric actuators,couplings among the input axes,and coupled linear and angular motions of the end effector.This paper presents an inverse hysteresis-coupling hybrid model to account for such hysteresis and couplings.First,a specially designed kinematic chain is adopted to transfer the pose of the end effector into the linear motions at three prismatic joints.Second,an inverse hysteresis-coupling hybrid model is developed to linearize and decouple the system via a multilayer feedforward neural network.A fractional-order PID controller is also integrated to improve the motion accuracy of the overall system.Experimental results demonstrate that the proposed method can accurately control the motion of the end effector with improved accuracy and robustness.展开更多
Flexure-based mechanisms are widely utilized in nano manipulations. The closed-form statics and dynamics modeling is difficult due to the complex topologies, the inevitable compliance of levers, the Hertzian contact i...Flexure-based mechanisms are widely utilized in nano manipulations. The closed-form statics and dynamics modeling is difficult due to the complex topologies, the inevitable compliance of levers, the Hertzian contact interface, etc. This paper presents the closed-form modeling of an XY nano-manipulator consisting of statically indeterminate symmetric(SIS) structures using leaf and circular flexure hinges. Theoretical analysis reveals that the lever’s compliance, the contact stiffness, and the load mass have significant influence on the static and dynamic performances of the system.Experiments are conducted to verify the effectiveness of the established models. If no piezoelectric actuator(PEA) is installed, the influence of the contact stiffness can be eliminated. Experimental results show that the estimation error on the output stiffness and first natural frequency can reach 2% and 1.7%, respectively. If PEAs are installed, the contact stiffness shows up in the models. As no effective method is currently available to measure or estimate the contact stiffness, it is impossible to precisely estimate the performance of the overall system. In this case, the established closed-form models can be utilized to calculate the bounds of the performance. The established closed-form models are widely applicable in the design and optimization of planar flexure-based mechanisms.展开更多
Updating parameters according to the driving rate of input, the rate-dependent Prandtl-Ishlinskii （PI） model is widely used in hysteresis modeling and compensation. In order to improve the modeling accuracy, two PI ...Updating parameters according to the driving rate of input, the rate-dependent Prandtl-Ishlinskii （PI） model is widely used in hysteresis modeling and compensation. In order to improve the modeling accuracy, two PI models identified at low and high driving rates separately are incorporated through a combination law. For the piezo- driven flexure-based mechanism, the very low damping ratio makes it easy to excite the structural vibration. As a re- suit, the measured hysteresis loop is greatly distorted and the modeling accuracy of the identified P1 model is signifi- cantly affected. In this paper, a novel time-efficient parameter identification method which utilizes the superimposed sinusoidal signals as the control input is proposed. This method effectively avoids the excitation of the structural vibra- tion. In addition, as the driving rate of the superimposed sinusoidal signals covers a wide range, all the coefficients required for modeling the rate-dependence can be identified through only one set of experimental data. Hysteresis modeling and trajectory tracking experiments were performed on a 2-DOF piezo-driven flexure-based mechanism. The experimental results show that the combined hysteresis model maintains the modeling accuracy over the entire work- ing range of the flexure-based mechanism. The mechanism＇s hysteresis is significantly suppressed by the use of the inverse PI model as the feedforward controller; and better result is achieved when a feedback loop is also incorporated. The tracking performance of the flexure-based mechanism is greatly improved.展开更多
基金supported in part by the Open Fund of State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment,Guangdong University of Technology(Grant No.JMDZ2021007)in part by the Guangdong International Cooperation Program of Science and Technology(Grant No.2022A0505050078).
文摘Planar positioning systems are widely utilized in micro and nano applications.The challenges in modeling and control of XYΘflexure-based mechanisms include hysteresis of the piezoelectric actuators,couplings among the input axes,and coupled linear and angular motions of the end effector.This paper presents an inverse hysteresis-coupling hybrid model to account for such hysteresis and couplings.First,a specially designed kinematic chain is adopted to transfer the pose of the end effector into the linear motions at three prismatic joints.Second,an inverse hysteresis-coupling hybrid model is developed to linearize and decouple the system via a multilayer feedforward neural network.A fractional-order PID controller is also integrated to improve the motion accuracy of the overall system.Experimental results demonstrate that the proposed method can accurately control the motion of the end effector with improved accuracy and robustness.
基金Supported by National Natural Science Foundation of China(Grant Nos.61403214,61327802,U1613220)Tianjin Provincial Natural Science Foundation of China(Grant Nos.14JCZDJC31800,14JCQNJC04700)
文摘Flexure-based mechanisms are widely utilized in nano manipulations. The closed-form statics and dynamics modeling is difficult due to the complex topologies, the inevitable compliance of levers, the Hertzian contact interface, etc. This paper presents the closed-form modeling of an XY nano-manipulator consisting of statically indeterminate symmetric(SIS) structures using leaf and circular flexure hinges. Theoretical analysis reveals that the lever’s compliance, the contact stiffness, and the load mass have significant influence on the static and dynamic performances of the system.Experiments are conducted to verify the effectiveness of the established models. If no piezoelectric actuator(PEA) is installed, the influence of the contact stiffness can be eliminated. Experimental results show that the estimation error on the output stiffness and first natural frequency can reach 2% and 1.7%, respectively. If PEAs are installed, the contact stiffness shows up in the models. As no effective method is currently available to measure or estimate the contact stiffness, it is impossible to precisely estimate the performance of the overall system. In this case, the established closed-form models can be utilized to calculate the bounds of the performance. The established closed-form models are widely applicable in the design and optimization of planar flexure-based mechanisms.
基金Supported by National Natural Science Foundation of China (No. 51175372)National Key Special Project of Science and Technology of China (No. 2011ZX04016-011)
文摘Updating parameters according to the driving rate of input, the rate-dependent Prandtl-Ishlinskii （PI） model is widely used in hysteresis modeling and compensation. In order to improve the modeling accuracy, two PI models identified at low and high driving rates separately are incorporated through a combination law. For the piezo- driven flexure-based mechanism, the very low damping ratio makes it easy to excite the structural vibration. As a re- suit, the measured hysteresis loop is greatly distorted and the modeling accuracy of the identified P1 model is signifi- cantly affected. In this paper, a novel time-efficient parameter identification method which utilizes the superimposed sinusoidal signals as the control input is proposed. This method effectively avoids the excitation of the structural vibra- tion. In addition, as the driving rate of the superimposed sinusoidal signals covers a wide range, all the coefficients required for modeling the rate-dependence can be identified through only one set of experimental data. Hysteresis modeling and trajectory tracking experiments were performed on a 2-DOF piezo-driven flexure-based mechanism. The experimental results show that the combined hysteresis model maintains the modeling accuracy over the entire work- ing range of the flexure-based mechanism. The mechanism＇s hysteresis is significantly suppressed by the use of the inverse PI model as the feedforward controller; and better result is achieved when a feedback loop is also incorporated. The tracking performance of the flexure-based mechanism is greatly improved.
