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基于PD的具有改进型线性扩张状态观测器的最优自抗扰控制器

PD-Based Optimal ADRC with Improved Linear Extended State Observer.

作者信息

Zhang Zhen, Cheng Jian, Guo Yinan

机构信息

School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China.

Research Institute of Mine Big Data, China Coal Research Institute, Beijing 100013, China.

出版信息

Entropy (Basel). 2021 Jul 13;23(7):888. doi: 10.3390/e23070888.

Abstract

Taking dead-zone nonlinearlity and external disturbances into account, an active disturbance rejection optimal controller based on a proportional-derivative (PD) control law is proposed by connecting the proportional-integral-derivative (PID) control, the active disturbance rejection control (ADRC) and particle swarm optimization (PSO), with the purpose of providing an efficient and practical technology, and improving the dynamic and steady-state control performances. Firstly, in order to eliminate the negative effects of the dead-zone, a class of 2-order typical single-input single-out system model is established after compensating the dead-zone. Following that, PD control law is introduced to replace the state error feedback control law in ADRC to simplify the control design. By analyzing the characteristics of the traditional linear extended state observer, an improved linear extended state observer is designed, with the purpose of improving the estimation performance of disturbances. Moreover, employing PSO with a designed objective function to optimize parameters of controller to improve control performance. Finally, ten comparative experiments are carried out to verify the effectiveness and superiority of the proposed controller.

摘要

考虑死区非线性和外部干扰,通过将比例积分微分(PID)控制、自抗扰控制(ADRC)和粒子群优化(PSO)相结合,提出了一种基于比例微分(PD)控制律的自抗扰最优控制器,旨在提供一种高效实用的技术,并改善动态和稳态控制性能。首先,为了消除死区的负面影响,在对死区进行补偿后建立了一类二阶典型单输入单输出系统模型。接着,引入PD控制律来替代ADRC中的状态误差反馈控制律,以简化控制设计。通过分析传统线性扩张状态观测器的特性,设计了一种改进的线性扩张状态观测器,以提高干扰估计性能。此外,采用具有设计目标函数的PSO来优化控制器参数,以改善控制性能。最后,进行了十次对比实验,以验证所提控制器的有效性和优越性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe7d/8306635/47e17133e1a0/entropy-23-00888-g001.jpg

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