Robust Kalman filtering for uncertain systems. (English) Zbl 0792.93118
Summary: This paper studies the problem of Kalman filter design for uncertain systems. The system under consideration is subjected to time-varying norm-bounded parameter uncertainties in both the state and measurement matrices. The problem we address is the design of a state estimator such that the covariance of the estimation error is guaranteed to be within a certain bound for all admissible uncertainties. A Riccati equation approach is proposed to solve the above problem. Furthermore, a suboptimal covariance upper bound can be computed by a convex optimization.
MSC:
| 93E11 | Filtering in stochastic control theory |
| 93B51 | Design techniques (robust design, computer-aided design, etc.) |
References:
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