Reduced-Order Model Approximation of Fractional-Order Systems Using Differential Evolution Algorithm

2017 ◽  
Vol 29 (1) ◽  
pp. 32-43 ◽  
Author(s):  
Bachir Bourouba ◽  
Samir Ladaci ◽  
Abdelhafid Chaabi
2021 ◽  
Author(s):  
Henghui Liang ◽  
Wei Yu ◽  
Rui Chen ◽  
Ying Luo

Abstract Although the active disturbance rejection controller can obtain good control performance without relying on specific model information, it targets integer-order systems. Fractional-order characteristics are commonly existed in practical systems. For fractional-order systems, it is more targeted to use the order information of the fractional-order model to design the active disturbance rejection controller, so as to obtain better control performance. A fractional active disturbance rejection controller composed of FOESO and FOPID (IDE-FOPID-FOESO) is proposed in this paper. The fractional-order extended state observer (FOESO) is designed based on the order information and the nonlinear state error feedback is replaced by the fractional-order PID controller (FOPID) whose parameters are obtained by the improved differential evolution algorithm (IDE). For IDE algorithm, the basis vector is randomly selected from the optimal individual population in the mutation strategy, and the scaling factor and cross-probability factor are adaptively adjusted according to the information of the successfully mutated individual in the search process to improve the exploration and mining capabilities of the algorithm. The simulation results show that the IDE algorithm can obtain the better parameters of FOPID faster compared with traditional DE algorithm and the IDE-FOPID-FOESO controller can be better applied to fractional-order systems with better control performance.


2016 ◽  
Vol 370-371 ◽  
pp. 538-550 ◽  
Author(s):  
Xiaojie Su ◽  
Xinxin Liu ◽  
Yong-Duan Song ◽  
Hak Keung Lam ◽  
Lei Wang

2021 ◽  
pp. 149-164
Author(s):  
Xiaojie Su ◽  
Yao Wen ◽  
Yue Yang ◽  
Peng Shi

2017 ◽  
Vol 2017 ◽  
pp. 1-13
Author(s):  
Li Lai ◽  
Yuan-Dong Ji ◽  
Su-Chuan Zhong ◽  
Lu Zhang

Using the dynamic properties of fractional-order Duffing system, a sequential parameter identification method based on differential evolution optimization algorithm is proposed for the fractional-order Duffing system. Due to the step by step parameter identification method, the dimension of parameter identification of each step is greatly reduced and the search capability of the differential evolution algorithm has been greatly improved. The simulation results show that the proposed method has higher convergence reliability and accuracy of identification and also has high robustness in the presence of measurement noise.


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