CAJ | 학술논문

对于带不确定噪声方差的线性离散时不变随机系统，根据极大极小鲁棒估计原理，基于带噪声方差保守上界的最坏情形保守系统，应用 Kalman 滤波和最优白噪声估计理论，提出了一种鲁棒稳态白噪声反卷积平滑器。对于所有容许的不确定噪声方差，保证它的实际平滑误差方差阵有一个最小上界。基于 Lyapunov 方程方法证明了它的鲁棒性和鲁棒精度关系。一个数值仿真例子验证了所提出结果的正确性和有效性。
대우대불학정조성방차적선성리산시불변수궤계통，근거겁대겁소로봉고계원리，기우대조성방차보수상계적최배정형보수계통，응용 Kalman 려파화최우백조성고계이론，제출료일충로봉은태백조성반권적평활기。대우소유용허적불학정조성방차，보증타적실제평활오차방차진유일개최소상계。기우 Lyapunov 방정방법증명료타적로봉성화로봉정도관계。일개수치방진례자험증료소제출결과적정학성화유효성。
For the linear discrete time-invariant stochastic system with uncertain noise variances,according to the minimax robust estimation principle,based on the worst-case conservative system with the conservative upper bounds of noise variances,applying Kalman filter and the optimal white noise estimation theory,a robust steady-state white noise deconvolution smoother is presented.Its actual smoothing error variances are guaran-teed to have a minimal upper bound for all admissible uncertain noise variances.Its robustness and the robust accuracy relation are proved based on the Lyapunov equation approach.A simulation example is given to verify the correctness and effectiveness of the proposed results.