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Stabilization of feedback control and stabilizability optimal solution for nonlinear quadratic problems

机译:非线性二次问题的反馈控制镇定和镇定性最优解

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This study refers to minimization of quadratic functionals in infinite time. The coefficients of the quadratic form are quadratic matrix, function of the state variable. Dynamic constraints are represented by bilinear differential systems of the form x = A(x)x + B(x)u, x(0) = x_0. One selects an adequate factorization of A(x) such that the analyzed system should be controllable. Employing the Hamilton-Jacobi equation it results the matrix algebraic equation of Riccati associated to the optimum problem. The necessary extremum conditions determine the adjoint variables λ and the control variables u as functions of state variable, as well as the adjoint system corresponding to those functions. Thus one obtains a matrix differential equation where the solution representing the positive defined symmetric matrix P(x), verifies the Riccati algebraic equation. The stability analysis for the autonomous systems solution resulting for the determined feedback control is performed using the Liapunov function method. Finally we present certain significant cases.
机译:这项研究指的是在无限时间内最小化二次函数。二次形式的系数是二次矩阵,是状态变量的函数。动态约束由形式为x = A(x)x + B(x)u,x(0)= x_0的双线性微分系统表示。选择一个适当的A(x)因式分解,使被分析的系统应可控。利用汉密尔顿-雅各比方程,可以得出与最佳问题有关的里卡蒂矩阵代数方程。必要的极值条件将伴随变量λ和控制变量u确定为状态变量的函数,以及与这些函数相对应的伴随系统。因此,获得一个矩阵微分方程,其中代表正定义对称矩阵P(x)的解验证了Riccati代数方程。使用Liapunov函数方法对确定的反馈控制进行的自治系统解决方案的稳定性分析。最后,我们介绍了一些重要案例。

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