This paper presents the application of iterative learning control (ILC) to compensate hysteresis in a piezoelectric actuator. The proposed controller is a hybrid of proportional-integral-differential (PID) control, wh...This paper presents the application of iterative learning control (ILC) to compensate hysteresis in a piezoelectric actuator. The proposed controller is a hybrid of proportional-integral-differential (PID) control, whose main function is for trajectory tracking, and a chatter-based ILC, whose main function is for hysteresis compensation. Stability analysis of the proposed ILC is presented, with the PID included in the dynamic of the piezoelectric actuator. The performance of the proposed controller is analysed through simulation and verified with experiment with a piezoelectric actuator.展开更多
A new dynamic model for cell-deformation-induced adenosine triphosphate （ATP） release from vascular endothelial cells （VECs） is proposed in this paper to quantify the relationship between the ATP concentration at ...A new dynamic model for cell-deformation-induced adenosine triphosphate （ATP） release from vascular endothelial cells （VECs） is proposed in this paper to quantify the relationship between the ATP concentration at the surface of VECs and blood flow-induced shear stress. The simulation results demonstrate that ATP concentration at the surface of VECs predicted by the proposed new dynamic model is more consistent with the experimental observations than those by the existing static and dynamic models. Furthermore, it is the first time that a proportional-integral-derivative （PID） feedback controller is applied to modulate extracellular ATP concentration. Three types of desired ATP concentration profiles including constant, square wave and sinusoid are obtained by regulating the wall shear stress under this PID control. The systematic methodology utilized in this paper to model and control ATP release from VECs via adjusting external stimulus opens up a new scenario where quantitative investigations into the underlying mechanisms for many biochemical phenomena can be carded out for the sake of controlling specific cellular events.展开更多
In this paper, we present an adaptive neuro-fuzzy controller design for a class of uncertain nonholonomic systems in the perturbed chained form with unknown virtual control coefficients and strong drift nonlinearities...In this paper, we present an adaptive neuro-fuzzy controller design for a class of uncertain nonholonomic systems in the perturbed chained form with unknown virtual control coefficients and strong drift nonlinearities. The robust adaptive neuro-fuzzy control laws are developed using state scaling and backstepping. Semiglobal uniform ultimate bound-edness of all the signals in the closed-loop are guaranteed, and the system states are proven to converge to a small neigh-borhood of zero. The control performance of the closed-loop system is guaranteed by appropriately choosing the design parameters. By using fuzzy logic approximation, the proposed control is free of control singularity problem. An adaptive control-based switching strategy is proposed to overcome the uncontrollability problem associated with x 0 (t 0 ) = 0.展开更多
文摘This paper presents the application of iterative learning control (ILC) to compensate hysteresis in a piezoelectric actuator. The proposed controller is a hybrid of proportional-integral-differential (PID) control, whose main function is for trajectory tracking, and a chatter-based ILC, whose main function is for hysteresis compensation. Stability analysis of the proposed ILC is presented, with the PID included in the dynamic of the piezoelectric actuator. The performance of the proposed controller is analysed through simulation and verified with experiment with a piezoelectric actuator.
基金supported by NUS Academic Research Fund (R-263-000-483-112)
文摘A new dynamic model for cell-deformation-induced adenosine triphosphate （ATP） release from vascular endothelial cells （VECs） is proposed in this paper to quantify the relationship between the ATP concentration at the surface of VECs and blood flow-induced shear stress. The simulation results demonstrate that ATP concentration at the surface of VECs predicted by the proposed new dynamic model is more consistent with the experimental observations than those by the existing static and dynamic models. Furthermore, it is the first time that a proportional-integral-derivative （PID） feedback controller is applied to modulate extracellular ATP concentration. Three types of desired ATP concentration profiles including constant, square wave and sinusoid are obtained by regulating the wall shear stress under this PID control. The systematic methodology utilized in this paper to model and control ATP release from VECs via adjusting external stimulus opens up a new scenario where quantitative investigations into the underlying mechanisms for many biochemical phenomena can be carded out for the sake of controlling specific cellular events.
文摘In this paper, we present an adaptive neuro-fuzzy controller design for a class of uncertain nonholonomic systems in the perturbed chained form with unknown virtual control coefficients and strong drift nonlinearities. The robust adaptive neuro-fuzzy control laws are developed using state scaling and backstepping. Semiglobal uniform ultimate bound-edness of all the signals in the closed-loop are guaranteed, and the system states are proven to converge to a small neigh-borhood of zero. The control performance of the closed-loop system is guaranteed by appropriately choosing the design parameters. By using fuzzy logic approximation, the proposed control is free of control singularity problem. An adaptive control-based switching strategy is proposed to overcome the uncontrollability problem associated with x 0 (t 0 ) = 0.
