The role and use of the stochastic linear-quadratic-Gaussian problem in control system design
暂无分享,去创建一个
[1] A. Sage,et al. Large and small scale sensitivity analysis of optimum estimation algorithms , 1968 .
[2] J. Potter. Matrix Quadratic Solutions , 1966 .
[3] W. Wonham. On the Separation Theorem of Stochastic Control , 1968 .
[4] D. Luenberger. A new derivation of the quadratic loss control equation , 1965 .
[5] D. Kleinman. On an iterative technique for Riccati equation computations , 1968 .
[6] J. Mendel. On the need for and use of a measure of state estimation errors in the design of quadratic-optimal control gains , 1971 .
[7] R. E. Kalman,et al. New Results in Linear Filtering and Prediction Theory , 1961 .
[8] R. Mehra. On the identification of variances and adaptive Kalman filtering , 1970 .
[9] C. Striebel. Sufficient statistics in the optimum control of stochastic systems , 1965 .
[10] I. Rhodes. A tutorial introduction to estimation and filtering , 1971 .
[11] R. Wishner,et al. Suboptimal state estimation for continuous-time nonlinear systems from discrete noisy measurements , 1968 .
[12] B. Friedland. Treatment of bias in recursive filtering , 1969 .
[13] R. E. Kalman,et al. Contributions to the Theory of Optimal Control , 1960 .
[14] R. E. Kalman,et al. A New Approach to Linear Filtering and Prediction Problems , 2002 .
[15] T. Nishimura. Error bounds of continuous Kalman filters and the application to orbit determination problems , 1967, IEEE Transactions on Automatic Control.