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• W1640963076 abstract "This thesis describes the development of an efficient algorithm for solvingnonlinear stochastic optimal control problems in discrete-time based on the principleof model-reality differences. The main idea is the integration of optimal control andparameter estimation. In this work, a simplified model-based optimal control modelwith adjustable parameters is constructed. As such, the optimal state estimate isapplied to design the optimal control law. The output is measured from the modeland used to adapt the adjustable parameters. During the iterative procedure, thedifferences between the real plant and the model used are captured by the adjustableparameters. The values of these adjustable parameters are updated repeatedly. In thisway, the optimal solution of the model will approach to the true optimum of theoriginal optimal control problem. Instead of solving the original optimal controlproblem, the model-based optimal control problem is solved. The algorithmdeveloped in this thesis contains three sub-algorithms. In the first sub-algorithm, thestate mean propagation removes the Gaussian white noise to obtain the expectedsolution. Furthermore, the accuracy of the state estimate with the smallest state errorcovariance is enhanced by using the Kalman filtering theory. This enhancementproduces the filtering solution by using the second sub-algorithm. In addition, animprovement is made in the third sub-algorithm where the minimum output residualis combined with the cost function. In this way, the real solution is closelyapproximated. Through the practical examples, the applicability, efficiency andeffectiveness of these integrated sub-algorithms have been demonstrated throughsolving several practical real world examples. In conclusion, the principle of modelrealitydifferences has been generalized to cover a range of discrete-time nonlinearoptimal control problems, both for deterministic and stochastic cases, based on theproposed modified linear optimal control theory." @default.
• W1640963076 created "2016-06-24" @default.
• W1640963076 creator A5088793444 @default.
• W1640963076 date "2011-06-01" @default.
• W1640963076 modified "2023-09-24" @default.
• W1640963076 title "Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems" @default.
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