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The design of a non-minimal state space fractional-order predictive functional controller for fractional systems of arbitrary order

机译:任意阶分数阶系统的非最小状态空间分数阶预测功能控制器的设计

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In this paper, the design of the fractional-order predictive functional controller ((PFC)-P-alpha) for the linear fractional systems of arbitrary order has been presented. For this purpose, at first, the fractional order transfer function has been digitized via Grunwald-Letnikov definition to obtain the linear regression model of the system. Next, the non-minimal input-output fractional-order state space ((NMSS)-N-alpha) model of the system has been derived. The fractional-order predictive functional controller ((PFC)-P-alpha) has been then designed for the (NMSS)-N-alpha model structure via defining a fractional order cost function over the fractional-order non-minimal state vector. Finally, genetic algorithm (GA) has been employed to obtain the optimal (PFC)-P-alpha control coefficients. The fractional-order model of two rods thermal bench has been considered as the uncertain case study in this paper. Simulation results for temperature control of this fractional-order system are representative of better performance of the designed controller with respect to the NMSSPFC as well as the fractional GPC. (C) 2015 Elsevier Ltd. All rights reserved.
机译:在本文中,提出了针对任意阶线性分数阶系统的分数阶预测功能控制器((PFC)-P-alpha)的设计。为此,首先,通过Grunwald-Letnikov定义将分数阶传递函数数字化,以获得系统的线性回归模型。接下来,导出了系统的非最小输入输出分数阶状态空间((NMSS)-N-alpha)模型。然后,通过在分数阶非最小状态向量上定义分数阶成本函数,针对(NMSS)-N-alpha模型结构设计分数阶预测功能控制器((PFC)-P-alpha)。最后,遗传算法(GA)已用于获得最佳(PFC)-P-alpha控制系数。本文将两杆热台的分数阶模型视为不确定的案例研究。该分数阶系统的温度控制仿真结果代表了所设计控制器相对于NMSSPFC以及分数GPC的更好性能。 (C)2015 Elsevier Ltd.保留所有权利。

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