Surge active control can expand the stable operating range of the compressor.However,the difficulty of flow measurement,dynamic uncertainty disturbance,actuator delay characteristics,hard constraints of control variab...Surge active control can expand the stable operating range of the compressor.However,the difficulty of flow measurement,dynamic uncertainty disturbance,actuator delay characteristics,hard constraints of control variable,and system security measures have not been fully considered in the existing active control system,which significantly hinders its engineering application.Therefore,a nonlinear model predictive surge active control method is first presented based on flow estimator designed by using a continuous-time Kalman filter for dealing with the hard constraint of control variable and the impact of actuator delay of compression system with dynamic uncertainty.Then,a high-safety active/surge passive hybrid control strategy is designed,dominated by the surge active control and supplemented by the surge passive control,to ensure the compression system’s safe and stable operation.Lastly,the simulation results suggest that the flow estimator accurately estimates the compressor flow.When considering the delay impact of the actuators and sensors and measurement noise on the system,the proposed method exhibits stronger robustness than the existing meth-ods.The active/surge passive hybrid control strategy can successfully ensure the compression system’s safe and stable operation.This paper is of high practical significance for the engineering application of future compressor surge active control technologies.展开更多
Active control of aero-engine turbine tip clearance is one of the best chances for engine performance uplift currently.To do that,the first requirement is real-time measurement of tip clearance in aero-engine working ...Active control of aero-engine turbine tip clearance is one of the best chances for engine performance uplift currently.To do that,the first requirement is real-time measurement of tip clearance in aero-engine working environment.However,turbine complexity makes it unlikely for tip clearance sensors to be loaded.In recognition of that,this paper proposed a model-based method for tip clearance measurement.Firstly,by considering previously wrongly neglected factors such as load deformation,a mathematical model to monitor dynamic tip clearance changes is built to improve calculation accuracy.Then,after clarifying the coupling relationship between engine models and tip clearance models,this paper builds a component-level mathematical model integrating dynamic characteristics of turbine tip clearance,which helps realize accurate measurement of tip clearance in working environment.How tip clearance affects turbine efficiency is studied afterwards and reported to aero-engine model,so as to mitigate performance difference between aero-engine model and real engines caused by turbine tip clearance.Lastly,by hardware-in-the-loop simulation,tip clearance model demonstrates 15.9%better accuracy than previously built models in terms of turbine centrifugal deformation calculation.As tip clearance measurement model takes averagely 0.34 ms in calculation,meeting the operation requirement,it proves to be an effective new way.展开更多
The onboard adaptive model can achieve the online real-time estimation of performance parameters that are difficult to measure in a real aero-engine,which is the key to realizing modelbased performance control.It must...The onboard adaptive model can achieve the online real-time estimation of performance parameters that are difficult to measure in a real aero-engine,which is the key to realizing modelbased performance control.It must possess satisfactory numerical stability and estimation accuracy.However,the positive definiteness of the state covariance matrix may be destroyed in filter estimation because of the existence of some uncertain factors,such as the accumulated measurement error,noise,and disturbance in the strongly nonlinear engine system,inevitably causing divergence of estimates of Cholesky decomposition-based Spherical Unscented Kalman Filter(SUKF).Therefore,this paper proposes an improved SUKF algorithm(iSUKF)and applies it to the performance degradation estimation of the engine.Compared to SUKF,the iSUKF mainly replaces the Cholesky decomposition with the Singular Value Decomposition(SVD),which is numerically stable without any strict requirement for the state covariance matrix.Meanwhile,a correction factor is designed to assess the measurement deviation between the real engine and the nonlinear onboard model to correct the state covariance matrix,thus maintaining better numerical stability of parameters estimated by the filter.Then,an offline correction strategy is also proposed to eliminate the influence of the degradation of unestimated health parameters or the filter’s inadequate estimation of the coupled health parameters.This action effectively promotes the onboard adaptive model’s estimation accuracy concerning the degradation of the engine’real health parameters and its performance parameters.Finally,the simulation results show that the iSUKF can maintain the numerical stability of the filter’s estimation of health parameters.Compared with the existing methods,the offline correction strategy improves the estimation accuracy of the iSUKF-based nonlinear onboard adaptive model for the performance parameters of the real engine by more than 50%.The proposed method will provide feasible technical support for model-based aero-engine performance control.展开更多
Formation keeping is important for multiple Unmanned Aerial Vehicles(multi-UAV)to fully play their roles in cooperative combats and improve their mission success rate.However,in practical applications,it is difficult ...Formation keeping is important for multiple Unmanned Aerial Vehicles(multi-UAV)to fully play their roles in cooperative combats and improve their mission success rate.However,in practical applications,it is difficult to achieve formation keeping precisely and obstacle avoidance autonomously at the same time.This paper proposes a joint control method based on robust H∞ controller and improved Artificial Potential Field(APF)method.Firstly,we build a formation flight model based on the “Leader-Follower”structure and design a robust H∞ controller with three channels X,Y and Z to eliminate dynamic uncertainties,so as to realize high-precision formation keeping.Secondly,to fulfill obstacle avoidance efficiently in complex situations where UAVs fly at high speed with high inertia,this paper comes up with the improved APF method with deformation factor considered.The judgment criterion is proposed and applied to ensure flight safety.In the end,the simulation results show that the designed controller is effective with the formation keeping a high accuracy and in the meantime,it enables UAVs to avoid obstacles autonomously and recover the formation rapidly when coming close to obstacles.Therefore,the method proposed here boasts good engineering application prospect.展开更多
基金supported by the National Natural Science Foundation of China(Nos.51906103,52176009).
文摘Surge active control can expand the stable operating range of the compressor.However,the difficulty of flow measurement,dynamic uncertainty disturbance,actuator delay characteristics,hard constraints of control variable,and system security measures have not been fully considered in the existing active control system,which significantly hinders its engineering application.Therefore,a nonlinear model predictive surge active control method is first presented based on flow estimator designed by using a continuous-time Kalman filter for dealing with the hard constraint of control variable and the impact of actuator delay of compression system with dynamic uncertainty.Then,a high-safety active/surge passive hybrid control strategy is designed,dominated by the surge active control and supplemented by the surge passive control,to ensure the compression system’s safe and stable operation.Lastly,the simulation results suggest that the flow estimator accurately estimates the compressor flow.When considering the delay impact of the actuators and sensors and measurement noise on the system,the proposed method exhibits stronger robustness than the existing meth-ods.The active/surge passive hybrid control strategy can successfully ensure the compression system’s safe and stable operation.This paper is of high practical significance for the engineering application of future compressor surge active control technologies.
基金supported by the National Natural Science Foundation of China(Nos.51906103,52176009).
文摘Active control of aero-engine turbine tip clearance is one of the best chances for engine performance uplift currently.To do that,the first requirement is real-time measurement of tip clearance in aero-engine working environment.However,turbine complexity makes it unlikely for tip clearance sensors to be loaded.In recognition of that,this paper proposed a model-based method for tip clearance measurement.Firstly,by considering previously wrongly neglected factors such as load deformation,a mathematical model to monitor dynamic tip clearance changes is built to improve calculation accuracy.Then,after clarifying the coupling relationship between engine models and tip clearance models,this paper builds a component-level mathematical model integrating dynamic characteristics of turbine tip clearance,which helps realize accurate measurement of tip clearance in working environment.How tip clearance affects turbine efficiency is studied afterwards and reported to aero-engine model,so as to mitigate performance difference between aero-engine model and real engines caused by turbine tip clearance.Lastly,by hardware-in-the-loop simulation,tip clearance model demonstrates 15.9%better accuracy than previously built models in terms of turbine centrifugal deformation calculation.As tip clearance measurement model takes averagely 0.34 ms in calculation,meeting the operation requirement,it proves to be an effective new way.
基金the National Natural Science Foundation of China(Nos.51906103,52176009).
文摘The onboard adaptive model can achieve the online real-time estimation of performance parameters that are difficult to measure in a real aero-engine,which is the key to realizing modelbased performance control.It must possess satisfactory numerical stability and estimation accuracy.However,the positive definiteness of the state covariance matrix may be destroyed in filter estimation because of the existence of some uncertain factors,such as the accumulated measurement error,noise,and disturbance in the strongly nonlinear engine system,inevitably causing divergence of estimates of Cholesky decomposition-based Spherical Unscented Kalman Filter(SUKF).Therefore,this paper proposes an improved SUKF algorithm(iSUKF)and applies it to the performance degradation estimation of the engine.Compared to SUKF,the iSUKF mainly replaces the Cholesky decomposition with the Singular Value Decomposition(SVD),which is numerically stable without any strict requirement for the state covariance matrix.Meanwhile,a correction factor is designed to assess the measurement deviation between the real engine and the nonlinear onboard model to correct the state covariance matrix,thus maintaining better numerical stability of parameters estimated by the filter.Then,an offline correction strategy is also proposed to eliminate the influence of the degradation of unestimated health parameters or the filter’s inadequate estimation of the coupled health parameters.This action effectively promotes the onboard adaptive model’s estimation accuracy concerning the degradation of the engine’real health parameters and its performance parameters.Finally,the simulation results show that the iSUKF can maintain the numerical stability of the filter’s estimation of health parameters.Compared with the existing methods,the offline correction strategy improves the estimation accuracy of the iSUKF-based nonlinear onboard adaptive model for the performance parameters of the real engine by more than 50%.The proposed method will provide feasible technical support for model-based aero-engine performance control.
基金supported by Funding from the National Key Laboratory of Rotorcraft Aeromechanics,China(No.61422202108)the National Natural Science Foundation of China(No.52176009).
文摘Formation keeping is important for multiple Unmanned Aerial Vehicles(multi-UAV)to fully play their roles in cooperative combats and improve their mission success rate.However,in practical applications,it is difficult to achieve formation keeping precisely and obstacle avoidance autonomously at the same time.This paper proposes a joint control method based on robust H∞ controller and improved Artificial Potential Field(APF)method.Firstly,we build a formation flight model based on the “Leader-Follower”structure and design a robust H∞ controller with three channels X,Y and Z to eliminate dynamic uncertainties,so as to realize high-precision formation keeping.Secondly,to fulfill obstacle avoidance efficiently in complex situations where UAVs fly at high speed with high inertia,this paper comes up with the improved APF method with deformation factor considered.The judgment criterion is proposed and applied to ensure flight safety.In the end,the simulation results show that the designed controller is effective with the formation keeping a high accuracy and in the meantime,it enables UAVs to avoid obstacles autonomously and recover the formation rapidly when coming close to obstacles.Therefore,the method proposed here boasts good engineering application prospect.