This paper proposes an optimization-based computational approach to design multi-rate observers for linear models of aerospace systems with asynchronous measurements.A case study on the estimation of the state of an a...This paper proposes an optimization-based computational approach to design multi-rate observers for linear models of aerospace systems with asynchronous measurements.A case study on the estimation of the state of an autonomous quadrotor UAV around its hovering operating point will be used as an example of the applicability of the proposed method.There are two theoretical contributions of the proposed method.The first is the derivation of a set of Linear Matrix Inequalities(LMIs)for the design of linear observers yielding convergence of the state estimation error given the maximum allowable sampling period(MASP)for each sensor.The second contribution is to propose an optimization problem subject to LMIs for finding the MASPs that guarantee exponential stability of the estimation error.The two contributions enable the analysis and design of multi-rate observers for systems with linear models,including quadrotor UAVs around a hovering operating point.The examples show a very intuitive result:as the sampling frequency of one sensor decreases,another sensor must sample faster to guarantee convergence of the estimated state to the real state.Simulations of a quadrotor with 12 states and 9 measurements show the effectiveness of the approach.展开更多
文摘This paper proposes an optimization-based computational approach to design multi-rate observers for linear models of aerospace systems with asynchronous measurements.A case study on the estimation of the state of an autonomous quadrotor UAV around its hovering operating point will be used as an example of the applicability of the proposed method.There are two theoretical contributions of the proposed method.The first is the derivation of a set of Linear Matrix Inequalities(LMIs)for the design of linear observers yielding convergence of the state estimation error given the maximum allowable sampling period(MASP)for each sensor.The second contribution is to propose an optimization problem subject to LMIs for finding the MASPs that guarantee exponential stability of the estimation error.The two contributions enable the analysis and design of multi-rate observers for systems with linear models,including quadrotor UAVs around a hovering operating point.The examples show a very intuitive result:as the sampling frequency of one sensor decreases,another sensor must sample faster to guarantee convergence of the estimated state to the real state.Simulations of a quadrotor with 12 states and 9 measurements show the effectiveness of the approach.
