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In this paper, an effective online method used for finite-horizon, nonlinear, stochastic tracking problems, is presented. The method incorporates the finite-horizon State Dependent Riccati Equation (SDRE) with Kaiman filter to account for the stochastic environment thereby extending the application spectrum to nonlinear systems and overcoming the hurdle with linear tracking systems limited to small...
A number of computational techniques have been offered for estimation of unmeasured states in nonlinear systems. Most of these techniques rely on applying the linear estimation techniques to the linearized systems, which can be effective only in the neighborhood of the operating point. This paper presents a new efficient approximate online technique used for finite-horizon nonlinear stochastic regulator...
In this paper, an online technique for finite-horizon nonlinear stochastic tracking problems is presented. The idea of the proposed technique is to integrate the Kalman filter algorithm and the State Dependent Riccati Equation (SDRE) technique. Unlike the ordinary methods which deal with the linearized system, this technique will estimate the unmeasured states of the nonlinear system directly, and...
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