In this paper, an efficient computational approach is proposed to solve the\ndiscrete time nonlinear stochastic optimal control problem. For this purpose,\na linear quadratic regulator model, which is a linear dynamical system with\nthe quadratic criterion cost function, is employed. In our approach, the model-\nbased optimal control problem is reformulated into the input-output equations.\nIn this way, the Hankel matrix and the observability matrix are constructed.\nFurther, the sum squares of output error is defined. In these point of\nviews, the least squares optimization problem is introduced, so as the differences\nbetween the real output and the model output could be calculated. Applying\nthe first-order derivative to the sum squares of output error, the necessary\ncondition is then derived. After some algebraic manipulations, the optimal\ncontrol law is produced. By substituting this control policy into the input-\noutput equations, the model output is updated iteratively. For illustration,\nan example of the direct current and alternating current converter problem is\nstudied. As a result, the model output trajectory of the least squares solution is\nclose to the real output with the smallest sum squares of output error. In conclusion,\nthe efficiency and the accuracy of the approach proposed are highly\npresented.
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