The Experts below are selected from a list of 10062 Experts worldwide ranked by ideXlab platform
Guangzheng Peng - One of the best experts on this subject based on the ideXlab platform.
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modeling and self tuning Pressure Regulator design for pneumatic Pressure load systems
Control Engineering Practice, 2007Co-Authors: Xuesong Wang, Yuhu Cheng, Guangzheng PengAbstract:Abstract This paper presents a dynamic model and a design method for an accurate self-tuning Pressure Regulator for pneumatic-Pressure–load systems that have some special characteristics such as being nonlinear and time-varying. A mathematical model is derived, which consists of a chamber continuity equation, an orifice flow equation and a force balance equation of the spool. Based on a theoretical analysis of the system dynamics, a three-order controlled auto-regressive moving average (CARMA) model is used to describe the practical Pressure–load systems. Then a linear quadratic Gaussian self-tuning Pressure Regulator is designed to realize an adaptive control of Pressure in the chamber. Because the system parameters are time-varying and the system states are difficult to detect, the recursive forgetting factor least-squares algorithm and the Kalman filtering method are adopted to estimate the system parameters and the system states. Experimental results show that the proposed self-tuning Pressure Regulator can be adapted to parameters which vary with such factors as the volume of the chamber and the setting Pressure and that better dynamic and static performances can be obtained.
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Modeling and self-tuning Pressure Regulator design for pneumatic-Pressure–load systems
Control Engineering Practice, 2007Co-Authors: Xuesong Wang, Yuhu Cheng, Guangzheng PengAbstract:Abstract This paper presents a dynamic model and a design method for an accurate self-tuning Pressure Regulator for pneumatic-Pressure–load systems that have some special characteristics such as being nonlinear and time-varying. A mathematical model is derived, which consists of a chamber continuity equation, an orifice flow equation and a force balance equation of the spool. Based on a theoretical analysis of the system dynamics, a three-order controlled auto-regressive moving average (CARMA) model is used to describe the practical Pressure–load systems. Then a linear quadratic Gaussian self-tuning Pressure Regulator is designed to realize an adaptive control of Pressure in the chamber. Because the system parameters are time-varying and the system states are difficult to detect, the recursive forgetting factor least-squares algorithm and the Kalman filtering method are adopted to estimate the system parameters and the system states. Experimental results show that the proposed self-tuning Pressure Regulator can be adapted to parameters which vary with such factors as the volume of the chamber and the setting Pressure and that better dynamic and static performances can be obtained.
Xuesong Wang - One of the best experts on this subject based on the ideXlab platform.
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modeling and self tuning Pressure Regulator design for pneumatic Pressure load systems
Control Engineering Practice, 2007Co-Authors: Xuesong Wang, Yuhu Cheng, Guangzheng PengAbstract:Abstract This paper presents a dynamic model and a design method for an accurate self-tuning Pressure Regulator for pneumatic-Pressure–load systems that have some special characteristics such as being nonlinear and time-varying. A mathematical model is derived, which consists of a chamber continuity equation, an orifice flow equation and a force balance equation of the spool. Based on a theoretical analysis of the system dynamics, a three-order controlled auto-regressive moving average (CARMA) model is used to describe the practical Pressure–load systems. Then a linear quadratic Gaussian self-tuning Pressure Regulator is designed to realize an adaptive control of Pressure in the chamber. Because the system parameters are time-varying and the system states are difficult to detect, the recursive forgetting factor least-squares algorithm and the Kalman filtering method are adopted to estimate the system parameters and the system states. Experimental results show that the proposed self-tuning Pressure Regulator can be adapted to parameters which vary with such factors as the volume of the chamber and the setting Pressure and that better dynamic and static performances can be obtained.
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Modeling and self-tuning Pressure Regulator design for pneumatic-Pressure–load systems
Control Engineering Practice, 2007Co-Authors: Xuesong Wang, Yuhu Cheng, Guangzheng PengAbstract:Abstract This paper presents a dynamic model and a design method for an accurate self-tuning Pressure Regulator for pneumatic-Pressure–load systems that have some special characteristics such as being nonlinear and time-varying. A mathematical model is derived, which consists of a chamber continuity equation, an orifice flow equation and a force balance equation of the spool. Based on a theoretical analysis of the system dynamics, a three-order controlled auto-regressive moving average (CARMA) model is used to describe the practical Pressure–load systems. Then a linear quadratic Gaussian self-tuning Pressure Regulator is designed to realize an adaptive control of Pressure in the chamber. Because the system parameters are time-varying and the system states are difficult to detect, the recursive forgetting factor least-squares algorithm and the Kalman filtering method are adopted to estimate the system parameters and the system states. Experimental results show that the proposed self-tuning Pressure Regulator can be adapted to parameters which vary with such factors as the volume of the chamber and the setting Pressure and that better dynamic and static performances can be obtained.
Yuhu Cheng - One of the best experts on this subject based on the ideXlab platform.
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modeling and self tuning Pressure Regulator design for pneumatic Pressure load systems
Control Engineering Practice, 2007Co-Authors: Xuesong Wang, Yuhu Cheng, Guangzheng PengAbstract:Abstract This paper presents a dynamic model and a design method for an accurate self-tuning Pressure Regulator for pneumatic-Pressure–load systems that have some special characteristics such as being nonlinear and time-varying. A mathematical model is derived, which consists of a chamber continuity equation, an orifice flow equation and a force balance equation of the spool. Based on a theoretical analysis of the system dynamics, a three-order controlled auto-regressive moving average (CARMA) model is used to describe the practical Pressure–load systems. Then a linear quadratic Gaussian self-tuning Pressure Regulator is designed to realize an adaptive control of Pressure in the chamber. Because the system parameters are time-varying and the system states are difficult to detect, the recursive forgetting factor least-squares algorithm and the Kalman filtering method are adopted to estimate the system parameters and the system states. Experimental results show that the proposed self-tuning Pressure Regulator can be adapted to parameters which vary with such factors as the volume of the chamber and the setting Pressure and that better dynamic and static performances can be obtained.
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Modeling and self-tuning Pressure Regulator design for pneumatic-Pressure–load systems
Control Engineering Practice, 2007Co-Authors: Xuesong Wang, Yuhu Cheng, Guangzheng PengAbstract:Abstract This paper presents a dynamic model and a design method for an accurate self-tuning Pressure Regulator for pneumatic-Pressure–load systems that have some special characteristics such as being nonlinear and time-varying. A mathematical model is derived, which consists of a chamber continuity equation, an orifice flow equation and a force balance equation of the spool. Based on a theoretical analysis of the system dynamics, a three-order controlled auto-regressive moving average (CARMA) model is used to describe the practical Pressure–load systems. Then a linear quadratic Gaussian self-tuning Pressure Regulator is designed to realize an adaptive control of Pressure in the chamber. Because the system parameters are time-varying and the system states are difficult to detect, the recursive forgetting factor least-squares algorithm and the Kalman filtering method are adopted to estimate the system parameters and the system states. Experimental results show that the proposed self-tuning Pressure Regulator can be adapted to parameters which vary with such factors as the volume of the chamber and the setting Pressure and that better dynamic and static performances can be obtained.
Keith G Lurie - One of the best experts on this subject based on the ideXlab platform.
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intrathoracic Pressure Regulator during continuous chest compression advanced cardiac resuscitation improves vital organ perfusion Pressures in a porcine model of cardiac arrest
Circulation, 2005Co-Authors: Demetris Yannopoulos, Vinay M Nadkarni, Scott Mcknite, Anu Rao, Kurt Kruger, Anja Metzger, David G Benditt, Keith G LurieAbstract:Background— A novel device, the intrathoracic Pressure Regulator (ITPR), combines an inspiratory impedance threshold device (ITD) with a vacuum source for the generation of controlled −10 mm Hg vac...
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intrathoracic Pressure Regulator during continuous chest compression advanced cardiac resuscitation improves vital organ perfusion Pressures in a porcine model of cardiac arrest
Circulation, 2005Co-Authors: Demetris Yannopoulos, Scott Mcknite, Kurt Kruger, Anja Metzger, David G Benditt, Vinay Nadkarni, Keith G LurieAbstract:Background— A novel device, the intrathoracic Pressure Regulator (ITPR), combines an inspiratory impedance threshold device (ITD) with a vacuum source for the generation of controlled −10 mm Hg vacuum in the trachea during cardiopulmonary resuscitation (CPR) while allowing positive Pressure ventilation. Compared with standard (STD) CPR, ITPR-CPR will enhance venous return, systemic arterial Pressure, and vital organ perfusion in both porcine models of ventricular fibrillation and hypovolemic cardiac arrest. Methods and Results— In protocol 1, 20 pigs (weight, 30±0.5 kg) were randomized to STD-CPR or ITPR-CPR. After 8 minutes of untreated ventricular fibrillation, CPR was performed for 6 minutes at 100 compressions per minute and positive Pressure ventilation (100% O2) with a compression-to-ventilation ratio of 15:2. In protocol 2, 6 animals were bled 50% of their blood volume. After 4 minutes of untreated ventricular fibrillation, interventions were performed for 2 minutes with STD-CPR and 2 minutes of IT...
Demetris Yannopoulos - One of the best experts on this subject based on the ideXlab platform.
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intrathoracic Pressure Regulator during continuous chest compression advanced cardiac resuscitation improves vital organ perfusion Pressures in a porcine model of cardiac arrest
Circulation, 2005Co-Authors: Demetris Yannopoulos, Vinay M Nadkarni, Scott Mcknite, Anu Rao, Kurt Kruger, Anja Metzger, David G Benditt, Keith G LurieAbstract:Background— A novel device, the intrathoracic Pressure Regulator (ITPR), combines an inspiratory impedance threshold device (ITD) with a vacuum source for the generation of controlled −10 mm Hg vac...
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intrathoracic Pressure Regulator during continuous chest compression advanced cardiac resuscitation improves vital organ perfusion Pressures in a porcine model of cardiac arrest
Circulation, 2005Co-Authors: Demetris Yannopoulos, Scott Mcknite, Kurt Kruger, Anja Metzger, David G Benditt, Vinay Nadkarni, Keith G LurieAbstract:Background— A novel device, the intrathoracic Pressure Regulator (ITPR), combines an inspiratory impedance threshold device (ITD) with a vacuum source for the generation of controlled −10 mm Hg vacuum in the trachea during cardiopulmonary resuscitation (CPR) while allowing positive Pressure ventilation. Compared with standard (STD) CPR, ITPR-CPR will enhance venous return, systemic arterial Pressure, and vital organ perfusion in both porcine models of ventricular fibrillation and hypovolemic cardiac arrest. Methods and Results— In protocol 1, 20 pigs (weight, 30±0.5 kg) were randomized to STD-CPR or ITPR-CPR. After 8 minutes of untreated ventricular fibrillation, CPR was performed for 6 minutes at 100 compressions per minute and positive Pressure ventilation (100% O2) with a compression-to-ventilation ratio of 15:2. In protocol 2, 6 animals were bled 50% of their blood volume. After 4 minutes of untreated ventricular fibrillation, interventions were performed for 2 minutes with STD-CPR and 2 minutes of IT...
