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Decentralized observer-based optimal control using two-point boundary value successive approximation approach application for a multimachine power system

机译:基于分散的观察者的最优控制,使用两点边界值连续近似方法应用于多机动力系统

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摘要

In this paper, we present a new decentralized observer for a class of nonlinear interconnected systems, based on an optimal control law using the two-point boundary value (TPBV) successive approximation approach. This technique, used previously to develop a nonlinear decentralized suboptimal control for a multimachine power system, inspired us to develop a new method to design a decentralized observer-based suboptimal control law for the same system. The TPBV approach is characterized by the transformation of each high order coupling nonlinear TPBV problem into a sequence of linear decoupling TPBV problems that uniformly converge to the optimal control for nonlinear interconnected large-scale systems. Sufficient conditions for the asymptotic stability of the developed feedback control scheme are proposed in terms of linear matrix inequalities (LMIs) constraints, which can be efficiently solved by the LMI optimization techniques, to compute the control and the observation gains of the overall system. We applied this approach to a three-machine power system which generators are nonlinear systems strongly interconnected. We demonstrated clearly, via advanced simulations, that this approach was able to bring good performances, improving effectively transient stability of this power system in few iterative sequences while allowing the reconstruction of its non-measurable state variables.
机译:在本文中,我们为一类非线性互连系统提供了一种新的分散观察者,基于使用两点边界值(TPBV)连续近似方法的最佳控制法。此技术以前为多机动力系统开发非线性分散的次优控制,启发了我们开发一种为同一系统设计分散的观察者的次优控制规律的新方法。 TPBV方法的特征在于将每个高阶耦合非线性TPBV问题的转换为一系列线性解耦TPBV问题,其均匀地收敛到非线性互连大型系统的最佳控制。就线性矩阵不等式(LMI)约束而提出了发育反馈控制方案的充分条件,其可以通过LMI优化技术有效解决,以计算控制和整个系统的观察增益。我们将这种方法应用于三机器电力系统,该系统是强烈互连的非线性系统。我们通过先进的模拟显然证明了这种方法能够带来良好的性能,在很少的迭代序列中提高该电力系统的有效稳定性,同时允许重建其不可测量的状态变量。

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