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Kalman Filtering With Inequality Constraints For Turbofan Engine Health Estimation, Daniel J. Simon, Donald L. Simon
Kalman Filtering With Inequality Constraints For Turbofan Engine Health Estimation, Daniel J. Simon, Donald L. Simon
Electrical and Computer Engineering Faculty Publications
Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state-variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. Thus, two analytical methods to incorporate state-variable inequality constraints into the Kalman filter are now derived. The first method is a general technique that uses hard constraints to enforce inequalities on the state-variable estimates. The resultant filter is a combination …
A Game Theory Approach To Constrained Minimax State Estimation, Daniel J. Simon
A Game Theory Approach To Constrained Minimax State Estimation, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
This paper presents a game theory approach to the constrained state estimation of linear discrete time dynamic systems. In the application of state estimators, there is often known model or signal information that is either ignored or dealt with heuristically. For example, constraints on the state values (which may be based on physical considerations) are often neglected because they do not easily fit into the structure of the state estimator. This paper develops a method for incorporating state equality constraints into a minimax state estimator. The algorithm is demonstrated on a simple vehicle tracking simulation.