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Differential flatness theory-based approach to the control of gas-turbine electric power generation units

机译:基于差分平坦度理论的燃气轮机发电机组控制方法

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A differential flatness theory-based control and state estimation method has been developed for electric power units that consist of synchronous generators connected to gas turbines. The dynamic model of the power unit satisfies the properties of differential flatness and this allows for its transformation into an input-output linearized form. Moreover, it is shown that the state-space description of the power system can be written in the canonical (Brunvsky) form. Using this, a solution for the power unit's control and state estimation problem is given. First, a stabilizing feedback controller is designed. Moreover, with the use of differential flatness theory-based implementation of the Kalman Filter it becomes possible to solve the state and disturbances estimation problem of the gas-turbine power unit. The considered filtering method, under the name of Derivative-free nonlinear Kalman Filter, consists of application of the Kalman Filter's recursion on the linearized equivalent model of the power system, and of an inverse transformation that allows for computing estimates for the state variables of the initial nonlinear system. By redesigning the aforementioned Kalman Filter as a disturbance observer one can also identify and annihilate in real time exogenous perturbations.
机译:对于由连接到燃气轮机的同步发电机组成的电力单元,已经开发了基于差分平坦度理论的控制和状态估计方法。功率单元的动态模型满足差分平坦度的特性,这使其可以转换为输入输出线性化形式。此外,还显示了电力系统的状态空间描述可以用规范形式(Brunvsky)编写。以此为基础,给出了功率单元控制和状态估计问题的解决方案。首先,设计了一个稳定的反馈控制器。而且,通过使用基于差分平坦度理论的卡尔曼滤波器的实现,有可能解决燃气轮机动力单元的状态和扰动估计问题。所考虑的滤波方法,以无导数非线性卡尔曼滤波器的名义,包括将卡尔曼滤波器的递归应用于电力系统的线性等效模型,以及进行逆变换的方法,该逆变换可用于计算电力系统状态变量的估计值。初始非线性系统。通过将上述卡尔曼滤波器重新设计为干扰观测器,人们还可以实时识别并消除外部干扰。

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