CAJ | 학술논문

针对连续非线性系统的参数估计问题，提出了改进的连续-离散无迹卡尔曼滤波算法。该算法结合系统状态和参数的估计均值和协方差阵，通过构建控制系统的无迹状态矩阵，并对无迹状态函数积分获得预测无迹状态阵，再经过均值解算和估计更新，获得参数的估计值。然后，针对水下航行器连续非线性控制系统的故障诊断问题，将水下航行器执行机构的故障，以比例系数和附加参数的形式表达在控制系统的状态空间方程中，通过采用改进的连续-离散无迹卡尔曼滤波算法，估计故障数据，实现执行机构的故障诊断。最后，在水下航行器回坞仿真实验中，采用该算法有效估计出执行机构故障，验证了算法的可行性和有效性。
침대련속비선성계통적삼수고계문제，제출료개진적련속-리산무적잡이만려파산법。해산법결합계통상태화삼수적고계균치화협방차진，통과구건공제계통적무적상태구진，병대무적상태함수적분획득예측무적상태진，재경과균치해산화고계경신，획득삼수적고계치。연후，침대수하항행기련속비선성공제계통적고장진단문제，장수하항행기집행궤구적고장，이비례계수화부가삼수적형식표체재공제계통적상태공간방정중，통과채용개진적련속-리산무적잡이만려파산법，고계고장수거，실현집행궤구적고장진단。최후，재수하항행기회오방진실험중，채용해산법유효고계출집행궤구고장，험증료산법적가행성화유효성。
To diagnose the faults of an underwater vehicle’ s continuous nonlinear system, we propose an improved continuous-discrete unscented Kalman filtering ( CDUKF) algorithm. Firstly, according to the estimation mean val-ues and covariance matrix of the state of the continuous nonlinear system and the parameters of its faults, we con-struct its unscented state matrices and forecast its unscented state array through integrating the unscented state dif-ferential functions. Then we obtain the estimation mean values and covariance matrix of its state and parameters through calculating the mean values and updating the estimation. Secondly, we fuse the faults of the actuator of the underwater vehicle into the continuous nonlinear system in the form of proportional coefficient or affixation parameter and estimate the parameters of the faults of the actuator through constructing respectively the state and the parame-ters of the CDUKF, thus diagnosing the faults of the actuator. Finally, to diagnose the faults of the actuator in simu-lating the docking of the underwater vehicle on a horizontal plane, we use the CDUKF algorithm to effectively esti-mate the faults of the underwater vehicle in their parameter form, thus verifying its feasibility and effectiveness.