Determination of optimal feedback gain matrix for a class of nonlinear systems

N. Bilgin, M. U. Salamci
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引用次数: 3

Abstract

The paper studies optimal control of a class of nonlinear systems with quadratic/non-quadratic cost functions and suggests a new methodology to determine the control gain matrix for the nonlinear system. The nonlinear system model is approximated as a sequence of linear time varying approximations in which the classical controller design methods can be utilized. Then, optimal control is designed for the approximated linear time varying system where the optimal control is determined to minimize a given cost function. The results of convergence of the successive linear time varying approximations to the nonlinear system are used and an optimal feedback gain matrix for the nonlinear system is obtained. The convergence of optimal control gain matrix designed for the successive linear time varying systems to a nonlinear gain matrix is proved. Once the gain matrix is determined from the successive approximations, then it is used as an optimal feedback gain matrix for the nonlinear system in a range of implementation domain. The method suggested in this study eliminates the disadvantages of the successive linear time varying approximation approach where the optimal control is obtained from a series of approximations for all implementation cases. The suggested methodology is compared with similar types of approximation based approaches studied in the literature.
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一类非线性系统最优反馈增益矩阵的确定
研究了一类具有二次/非二次代价函数的非线性系统的最优控制问题,提出了一种确定非线性系统控制增益矩阵的新方法。将非线性系统模型近似为一系列线性时变近似,其中可以使用经典的控制器设计方法。然后,设计了近似线性时变系统的最优控制,其中最优控制确定为最小化给定的代价函数。利用非线性系统连续线性时变逼近的收敛性结果,得到了非线性系统的最优反馈增益矩阵。证明了连续线性时变系统的最优控制增益矩阵收敛于一个非线性增益矩阵。一旦从逐次逼近中确定增益矩阵,就可以将其作为非线性系统在一定实现域内的最优反馈增益矩阵。该方法消除了逐次线性时变逼近方法的缺点,即对所有的实现情况都通过一系列的逼近来获得最优控制。建议的方法与文献中研究的类似类型的近似方法进行了比较。
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