This article deals with the disturbance attenuation control of aircraft flying through wind shear via Linear Parameter Varying(LPV) modeling and control method. A Flight Dynamics Model(FDM) with wind shear effects con...This article deals with the disturbance attenuation control of aircraft flying through wind shear via Linear Parameter Varying(LPV) modeling and control method. A Flight Dynamics Model(FDM) with wind shear effects considered was established in wind coordinate system. An LPV FDM was built up based on function substitution whose decomposing function was optimized by Genetic Algorithm(GA). The wind disturbance was explicitly included in the system matrix of LPV FDM. Taking wind disturbance as external uncertainties, robust LPV control method with the LPV FDM was put forward. Based on ride quality and flight safety requirements in wind disturbance, longitudinal and lateral output feedback robust LPV controllers were designed respectively,in which the scheduling flight states in LPV model were actually dependent parameters in LPV control. The results indicate that LPV FDM can reflect the instantaneous dynamics of nonlinear system especially at the boundary of aerodynamic envelope. Furthermore, the LPV FDM also can approach nonlinear FDM’s response in wind disturbance special flight. Compared with a parameter-invariant LQR controller designed with a small-disturbance FDM, the LPV controllers show preferable robustness and stability for disturbance attenuation.展开更多
The precise control of turbofan engines thrust is an important guarantee for an aircraft to obtain good flight performance and a challenge due to complex nonlinear dynamics of engines and time-varying parameters. The ...The precise control of turbofan engines thrust is an important guarantee for an aircraft to obtain good flight performance and a challenge due to complex nonlinear dynamics of engines and time-varying parameters. The main difficulties lie in the following two aspects. Firstly, it is hard to obtain an accurate kinetic model for the turbofan engine. Secondly, some model parameters often change in different flight conditions and states and even fluctuate sharply in some cases. These variable parameters bring huge challenge for the turbofan engine control. To solve the turbofan engine control problem, this paper presents a non-affine parameter-dependent Linear Parameter Varying(LPV) model-based adaptive control approach. In this approach, polynomial-based LPV modeling method is firstly employed to obtain the basis matrices, and then the Radial Basis Function Neural Networks(RBFNN) is introduced for the online estimation of the non-affine model parameters to improve the simulation performance. LPV model-based Linear Matrix Inequality(LMI) control method is applied to derive the control law. A robust control term is introduced to fix the estimation error of the nonlinear time-varying model parameters for better control performance. Finally, the Lyapunov stability analysis is performed to ensure the asymptotical convergence of the closed loop system. The simulation results show that the states of the engine can change smoothly and the thrust of the engine can accurately follow the desired trajectory, indicating that the proposed control approach is effective. The contribution of this work lies in the combination of linear system control and nonlinear system control methods to design an effective controller for the turbofan engine and to provide a new way for turbofan engine control research.展开更多
To solve the problem of robust servo performance of Flight Environment Testbed(FET)of Altitude Ground Test Facilities(AGTF) over the whole operational envelope, a two-degree-offreedom μ synthesis method based on Line...To solve the problem of robust servo performance of Flight Environment Testbed(FET)of Altitude Ground Test Facilities(AGTF) over the whole operational envelope, a two-degree-offreedom μ synthesis method based on Linear Parameter Varying(LPV) schematic is proposed, and meanwhile a new structure frame of μ synthesis control on two degrees of freedom with double integral and weighting functions is presented, which constitutes a core support part of the paper. Aimed at the problem of reference command's rapid change, one freedom feed forward is adopted, while another freedom output feedback is used to meet good servo tracking as well as disturbance and noise rejection; furthermore, to overcome the overshoot problem and acquire dynamic tuning,the integral is introduced in inner loop, and another integral controller is used in outer loop in order to guarantee steady errors; additionally, two performance weighting functions are designed to achieve robust specialty and control energy limit considering the uncertainties in system. As the schedule parameters change over large flight envelope, the stability of closed-loop LPV system is proved using Lyapunov inequalities. The simulation results show that the relative tracking errors of temperature and pressure are less than 0.5% with LPV μ synthesis controller. Meanwhile, compared with non-LPV μ synthesis controller in large uncertainty range, the proposed approach in this research can ensure robust servo performance of FET over the whole operational envelope.展开更多
针对风力机在额定风速以下效率较低以及风速不确定的问题,提出最大功率捕获(maximum power point tracking, MPPT)下的多胞形控制器设计方法。考虑到风力机气动系统具有高度非线性,利用雅克比线性化和凸分解技术,以气动转矩的偏导参数...针对风力机在额定风速以下效率较低以及风速不确定的问题,提出最大功率捕获(maximum power point tracking, MPPT)下的多胞形控制器设计方法。考虑到风力机气动系统具有高度非线性,利用雅克比线性化和凸分解技术,以气动转矩的偏导参数为调度变量,将风力机系统转换为具有多胞形结构的线性变参数(linearparametervarying,LPV)模型,并通过求解线性矩阵不等式(linear matrix inequalities, LMIs)得到具有多胞形结构的LPV控制器。仿真结果表明,所设计的控制器既能保证系统在额定风速以下实现MPPT捕获,又具有很强的鲁棒性。展开更多
基金co-supported by the National Natural Science Foundation of China(Nos.U1533120 and U1733122)the Fundamental Research Funds for the Central Universities of China(No.NS2015066)
文摘This article deals with the disturbance attenuation control of aircraft flying through wind shear via Linear Parameter Varying(LPV) modeling and control method. A Flight Dynamics Model(FDM) with wind shear effects considered was established in wind coordinate system. An LPV FDM was built up based on function substitution whose decomposing function was optimized by Genetic Algorithm(GA). The wind disturbance was explicitly included in the system matrix of LPV FDM. Taking wind disturbance as external uncertainties, robust LPV control method with the LPV FDM was put forward. Based on ride quality and flight safety requirements in wind disturbance, longitudinal and lateral output feedback robust LPV controllers were designed respectively,in which the scheduling flight states in LPV model were actually dependent parameters in LPV control. The results indicate that LPV FDM can reflect the instantaneous dynamics of nonlinear system especially at the boundary of aerodynamic envelope. Furthermore, the LPV FDM also can approach nonlinear FDM’s response in wind disturbance special flight. Compared with a parameter-invariant LQR controller designed with a small-disturbance FDM, the LPV controllers show preferable robustness and stability for disturbance attenuation.
基金supported by the National Natural Science Foundation of China(No.51766011)the Aeronautical Science Foundation of China(No.2014ZB56002)
文摘The precise control of turbofan engines thrust is an important guarantee for an aircraft to obtain good flight performance and a challenge due to complex nonlinear dynamics of engines and time-varying parameters. The main difficulties lie in the following two aspects. Firstly, it is hard to obtain an accurate kinetic model for the turbofan engine. Secondly, some model parameters often change in different flight conditions and states and even fluctuate sharply in some cases. These variable parameters bring huge challenge for the turbofan engine control. To solve the turbofan engine control problem, this paper presents a non-affine parameter-dependent Linear Parameter Varying(LPV) model-based adaptive control approach. In this approach, polynomial-based LPV modeling method is firstly employed to obtain the basis matrices, and then the Radial Basis Function Neural Networks(RBFNN) is introduced for the online estimation of the non-affine model parameters to improve the simulation performance. LPV model-based Linear Matrix Inequality(LMI) control method is applied to derive the control law. A robust control term is introduced to fix the estimation error of the nonlinear time-varying model parameters for better control performance. Finally, the Lyapunov stability analysis is performed to ensure the asymptotical convergence of the closed loop system. The simulation results show that the states of the engine can change smoothly and the thrust of the engine can accurately follow the desired trajectory, indicating that the proposed control approach is effective. The contribution of this work lies in the combination of linear system control and nonlinear system control methods to design an effective controller for the turbofan engine and to provide a new way for turbofan engine control research.
文摘To solve the problem of robust servo performance of Flight Environment Testbed(FET)of Altitude Ground Test Facilities(AGTF) over the whole operational envelope, a two-degree-offreedom μ synthesis method based on Linear Parameter Varying(LPV) schematic is proposed, and meanwhile a new structure frame of μ synthesis control on two degrees of freedom with double integral and weighting functions is presented, which constitutes a core support part of the paper. Aimed at the problem of reference command's rapid change, one freedom feed forward is adopted, while another freedom output feedback is used to meet good servo tracking as well as disturbance and noise rejection; furthermore, to overcome the overshoot problem and acquire dynamic tuning,the integral is introduced in inner loop, and another integral controller is used in outer loop in order to guarantee steady errors; additionally, two performance weighting functions are designed to achieve robust specialty and control energy limit considering the uncertainties in system. As the schedule parameters change over large flight envelope, the stability of closed-loop LPV system is proved using Lyapunov inequalities. The simulation results show that the relative tracking errors of temperature and pressure are less than 0.5% with LPV μ synthesis controller. Meanwhile, compared with non-LPV μ synthesis controller in large uncertainty range, the proposed approach in this research can ensure robust servo performance of FET over the whole operational envelope.
文摘针对风力机在额定风速以下效率较低以及风速不确定的问题,提出最大功率捕获(maximum power point tracking, MPPT)下的多胞形控制器设计方法。考虑到风力机气动系统具有高度非线性,利用雅克比线性化和凸分解技术,以气动转矩的偏导参数为调度变量,将风力机系统转换为具有多胞形结构的线性变参数(linearparametervarying,LPV)模型,并通过求解线性矩阵不等式(linear matrix inequalities, LMIs)得到具有多胞形结构的LPV控制器。仿真结果表明,所设计的控制器既能保证系统在额定风速以下实现MPPT捕获,又具有很强的鲁棒性。
