Radar leveling system is the key equipment for improving the radar mobility and survival capability. A combined quantitative feedback theory (QFT) controller is designed for the radar truck leveling simulator in this ...Radar leveling system is the key equipment for improving the radar mobility and survival capability. A combined quantitative feedback theory (QFT) controller is designed for the radar truck leveling simulator in this paper, which suffers from strong nonlinearities and system parameter uncertainties. QFT can reduce the plant uncertainties and stabilize the system, but it fails to obtain high-precision tracking. This drawback can be solved by a robust QFT control scheme based on zero phase error tracking control (ZPETC) compensation. The combined controller not only possesses high robustness, but greatly improves the system performance. To verify the effiectiveness and the potential of the proposed controller, a series of experiments have been carried out. Experimental results have demonstrated its robustness against a large range of parameters variation and high tracking precision performance, as well as its capability of restraining the load coupling among channels. The combined QFT controller can drive the radar truck leveling platform accurately, quickly and stably.展开更多
Each joint of a hydraulic-driven legged robot adopts a highly integrated hydraulic drive unit(HDU),which features a high power-weight ratio.However,most HDUs are throttling-valve-controlled cylinder systems,which exhi...Each joint of a hydraulic-driven legged robot adopts a highly integrated hydraulic drive unit(HDU),which features a high power-weight ratio.However,most HDUs are throttling-valve-controlled cylinder systems,which exhibit high energy losses.By contrast,pump control systems offer a high efficiency.Nevertheless,their response ability is unsatisfactory.To fully utilize the advantages of pump and valve control systems,in this study,a new type of pump-valve compound drive system(PCDS)is designed,which can not only effectively reduce the energy loss,but can also ensure the response speed and response accuracy of the HDUs in robot joints to satisfy the performance requirements of robots.Herein,considering the force control requirements of energy conservation,high precision,and fast response of the robot joint HDU,a nonlinear mathematical model of the PCDS force control system is first introduced.In addition,pressure-flow nonlinearity,friction nonlinearity,load complexity and variability,and other factors affecting the system are considered,and a novel force control method based on quantitative feedback theory(QFT)and a disturbance torque observer(DTO)is designed,which is denoted as QFT-DTOC herein.This method improves the control accuracy and robustness of the force control system,reduces the effect of the disturbance torque on the control performance of the servo motor,and improves the overall force control performance of the system.Finally,experimental verification is performed using the PCDS performance test platform.The experimental results and quantitative data show that the QFT-DTOC proposed herein can significantly improve the force control performance of the PCDS.The relevant force control method can be used as a bottom-control method for the hydraulic servo system to provide a foundation for implementing the top-level trajectory planning of the robot.展开更多
In order to meet tracking performance index of three-axis hydraulic simulator, based on classical quantitative feedback theory （QFT）, an improved QFT technique is used to synthesize controller of low gain and bandwi...In order to meet tracking performance index of three-axis hydraulic simulator, based on classical quantitative feedback theory （QFT）, an improved QFT technique is used to synthesize controller of low gain and bandwidth. By choosing a special nominal plant, the improved method assigns relative magnitude and phase tracking error between system uncertainty and nominal control plant. Relative tracking error induced by system uncertainty is transformed into sensitivity problem and relative tracking error induced by nominal plant forms into a region on Nichols chart. The two constraints further form into a combined bound which is fit for magnitude and phase loop shaping. Because of leaving out pre-filter of classical QFT controller structure, tracking performance is enhanced greatly. Furthermore, a cascaded two-loop control strategy is proposed to heighten control effect. The improved technique＇s efficacy is validated by simulation and experiment results.展开更多
A novel method of incorporating generalized predictive control (GPC) algorithms based on quantitative feedback theory (QFT) principles is proposed for solving the feedback control problem of the highly uncertain and c...A novel method of incorporating generalized predictive control (GPC) algorithms based on quantitative feedback theory (QFT) principles is proposed for solving the feedback control problem of the highly uncertain and cross-coupling plants. The quantitative feedback theory decouples the multi-input and multi-output (MIMO) plant and is also used to reduce the uncertainties of the system, stabilize the system, and achieve tracking performance of the system to a certain extent. Single-input and single-output (SISO) generalized predictive control is used to achieve performance with higher performance. In GPC, the model is identified on-line, which is based on the QFT input and the plant output signals. The simulation results show that the performance of the system is superior to the performance when only QFT is used for highly uncertain MIMO plants.展开更多
A novel method of incorporating generalized predictive control GPC algorithms based on quantitative feedback theory QFT principles is proposed for solving the feedback control problem of the highly uncertain and cross...A novel method of incorporating generalized predictive control GPC algorithms based on quantitative feedback theory QFT principles is proposed for solving the feedback control problem of the highly uncertain and cross-coupling plants. The quantitative feedback theory decouples the multi-input and multi-output MIMO plant and is also used to reduce the uncertainties of the system, stabilize the system, and achieve tracking performance of the system to a certain extent. Single-input and single-output SISO generalized predictive control is used to achieve performance with higher performance. In GPC, the model is identified on-line, which is based on the QFT input and the plant output signals. The simulation results show that the performance of the system is superior to the performance when only QFT is used for highly uncertain MIMO plants.展开更多
提出了一种M IM O定量反馈理论与特征值配置相结合的鲁棒解耦控制方法,该方法首先利用特征值配置使系统达到性能指标要求,通过对特征向量的限制实现M IM O系统解耦,然后利用QFT方法使其具备鲁棒性。通过对某型飞机侧向通道的仿真表明:...提出了一种M IM O定量反馈理论与特征值配置相结合的鲁棒解耦控制方法,该方法首先利用特征值配置使系统达到性能指标要求,通过对特征向量的限制实现M IM O系统解耦,然后利用QFT方法使其具备鲁棒性。通过对某型飞机侧向通道的仿真表明:该方法不仅解耦效果良好,而且具有较强的鲁棒性。展开更多
文摘Radar leveling system is the key equipment for improving the radar mobility and survival capability. A combined quantitative feedback theory (QFT) controller is designed for the radar truck leveling simulator in this paper, which suffers from strong nonlinearities and system parameter uncertainties. QFT can reduce the plant uncertainties and stabilize the system, but it fails to obtain high-precision tracking. This drawback can be solved by a robust QFT control scheme based on zero phase error tracking control (ZPETC) compensation. The combined controller not only possesses high robustness, but greatly improves the system performance. To verify the effiectiveness and the potential of the proposed controller, a series of experiments have been carried out. Experimental results have demonstrated its robustness against a large range of parameters variation and high tracking precision performance, as well as its capability of restraining the load coupling among channels. The combined QFT controller can drive the radar truck leveling platform accurately, quickly and stably.
基金Supported by National Excellent Natural Science Foundation of China(Grant No.52122503)Hebei Provincial Natural Science Foundation of China(Grant No.E2022203002)+2 种基金The Yanzhao’s Young Scientist Project of China(Grant No.E2023203258)Science Research Project of Hebei Education Department of China(Grant No.BJK2022060)Hebei Provincial Graduate Innovation Funding Project of China(Grant No.CXZZSS2022129).
文摘Each joint of a hydraulic-driven legged robot adopts a highly integrated hydraulic drive unit(HDU),which features a high power-weight ratio.However,most HDUs are throttling-valve-controlled cylinder systems,which exhibit high energy losses.By contrast,pump control systems offer a high efficiency.Nevertheless,their response ability is unsatisfactory.To fully utilize the advantages of pump and valve control systems,in this study,a new type of pump-valve compound drive system(PCDS)is designed,which can not only effectively reduce the energy loss,but can also ensure the response speed and response accuracy of the HDUs in robot joints to satisfy the performance requirements of robots.Herein,considering the force control requirements of energy conservation,high precision,and fast response of the robot joint HDU,a nonlinear mathematical model of the PCDS force control system is first introduced.In addition,pressure-flow nonlinearity,friction nonlinearity,load complexity and variability,and other factors affecting the system are considered,and a novel force control method based on quantitative feedback theory(QFT)and a disturbance torque observer(DTO)is designed,which is denoted as QFT-DTOC herein.This method improves the control accuracy and robustness of the force control system,reduces the effect of the disturbance torque on the control performance of the servo motor,and improves the overall force control performance of the system.Finally,experimental verification is performed using the PCDS performance test platform.The experimental results and quantitative data show that the QFT-DTOC proposed herein can significantly improve the force control performance of the PCDS.The relevant force control method can be used as a bottom-control method for the hydraulic servo system to provide a foundation for implementing the top-level trajectory planning of the robot.
文摘In order to meet tracking performance index of three-axis hydraulic simulator, based on classical quantitative feedback theory （QFT）, an improved QFT technique is used to synthesize controller of low gain and bandwidth. By choosing a special nominal plant, the improved method assigns relative magnitude and phase tracking error between system uncertainty and nominal control plant. Relative tracking error induced by system uncertainty is transformed into sensitivity problem and relative tracking error induced by nominal plant forms into a region on Nichols chart. The two constraints further form into a combined bound which is fit for magnitude and phase loop shaping. Because of leaving out pre-filter of classical QFT controller structure, tracking performance is enhanced greatly. Furthermore, a cascaded two-loop control strategy is proposed to heighten control effect. The improved technique＇s efficacy is validated by simulation and experiment results.
基金Supported by the National Natural Science Foundation of China (No.60374037, No.60574036), the Program for New Century Excellent Talents in Education Ministry (NCET), and the Specialized Research Fund for the Doctoral Program of Higher Education of China (No.20050055013).
文摘A novel method of incorporating generalized predictive control (GPC) algorithms based on quantitative feedback theory (QFT) principles is proposed for solving the feedback control problem of the highly uncertain and cross-coupling plants. The quantitative feedback theory decouples the multi-input and multi-output (MIMO) plant and is also used to reduce the uncertainties of the system, stabilize the system, and achieve tracking performance of the system to a certain extent. Single-input and single-output (SISO) generalized predictive control is used to achieve performance with higher performance. In GPC, the model is identified on-line, which is based on the QFT input and the plant output signals. The simulation results show that the performance of the system is superior to the performance when only QFT is used for highly uncertain MIMO plants.
基金the National Natural Science Foundation of China (No.60374037, No.60574036)the Program for New CenturyExcellent Talents in Education Ministry (NCET)the Specialized Research Fund for the Doctoral Program of Higher Edu-cation of China (No.20050055013)
文摘A novel method of incorporating generalized predictive control GPC algorithms based on quantitative feedback theory QFT principles is proposed for solving the feedback control problem of the highly uncertain and cross-coupling plants. The quantitative feedback theory decouples the multi-input and multi-output MIMO plant and is also used to reduce the uncertainties of the system, stabilize the system, and achieve tracking performance of the system to a certain extent. Single-input and single-output SISO generalized predictive control is used to achieve performance with higher performance. In GPC, the model is identified on-line, which is based on the QFT input and the plant output signals. The simulation results show that the performance of the system is superior to the performance when only QFT is used for highly uncertain MIMO plants.
