【摘要】 提出了一种基于机载非线性发动机模型,且具有输入端积分补偿的卡尔曼滤波器估计器的发动机自适应模型设计方法。其主旨是经过相似变换,在非线性相对弱化的另一坐标区域内设计常规卡尔曼滤波估计器,利用所得卡尔曼估计器对各估计回路的初步解耦,进一步在各观测回路中引入输入误差积分激励,对滤波器的输入进行实时积分修正,充分实现各估计参数回路的静态解耦。同时,将该卡尔曼滤波器与机载非线性实时模型综合,从而使发动机自适应模型具有大范围无静差参数跟踪能力。最后,对所提出建立的自适应模型的参数估计能力和鲁棒性进行了数字仿真验证。更多还原

【Abstract】 A new type of engine adaptive mode is proposed to tracking necessary performance degradations and evaluating engine immeasurable parameters,and it is improved by including Kalman filter and having the performance parameter as adjustable ones.The main idea to design the adaptive model is to firstly transform the original dynamic system to another coordinate system which has less nonlinearity,and then in the new space the Kaman filter is designed to eliminate the coupling among all the loops to some extent,and further an added inspiration including error integration is introduced to estimate parameter loop to eliminate static decoupling entirely.The Kalman filter is combined with the nonlinear engine model to realize no error tracking for engine part degradations in a large working scale.At last,some numerical simulations were carried out to verify the convergence capability and robustness of the proposed engine adaptive model.更多还原