引用本文: | 徐 敏,康 哲,刘早富.基于观测器的混沌电力系统PI固定时间自适应滑模控制[J].电力系统保护与控制,2022,50(19):146-157.[点击复制] |
XU Min, KANG Zhe, LIU Zaofu.Observer-based PI fixed time adaptive sliding mode control for chaotic power systems[J].Power System Protection and Control,2022,50(19):146-157[点击复制] |
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摘要: |
为对九阶电力系统中的混沌现象进行控制,基于有限时间观测器将PI控制与固定时间终端滑模控制相结合,提出一种控制电力系统混沌的新方法。有限时间观测器可对外来干扰进行预估,积分的加入可消除系统稳态误差。同时对传统滑模的固定切换控制项通过加入自适应律从而进行改进,进一步加强控制方法鲁棒性。利用tanh(x/τ)函数代替传统滑模的符号函数以及利用新的趋近律来解决滑模控制中的抖振现象。最后为缩减控制参数寻找时间,在构建一种新的目标函数基础上利用改进蚁狮算法对控制参数进行寻优。结果表明所提出的控制方法具有良好的控制性能。 |
关键词: 混沌控制 有限时间观测器 固定时间滑模 PI控制 蚁狮算法 |
DOI:DOI: 10.19783/j.cnki.pspc.211651 |
投稿时间:2021-12-04修订日期:2022-04-02 |
基金项目:国家自然科学基金项目资助(51967013) |
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Observer-based PI fixed time adaptive sliding mode control for chaotic power systems |
XU Min,KANG Zhe,LIU Zaofu |
(School of Information Engineering, Nanchang University, Nanchang 330000, China) |
Abstract: |
To control a chaotic phenomenon in the ninth-order power system, a new method for controlling the chaos of the power system is proposed. This combines PI control and fixed-time terminal sliding mode control based on a finite-time observer. The finite-time observer can predict the external disturbance, and the addition of the integral can eliminate the steady-state error of the system. The fixed switching control term of the traditional sliding mode is improved by adding an adaptive law to further enhance the robustness of the control method. The tanh(x/τ) function is used to replace the sign function of the traditional sliding mode and a new convergence law is used to solve the chattering phenomenon in the sliding mode control. Finally, in order to reduce the control parameter search time, a new objective function is constructed based on an improved ant-lion algorithm to find the optimal control parameters. The results show that the proposed control method has good control performance.
This work is supported by the National Natural Science Foundation of China (No. 51967013). |
Key words: chaos control finite time observer fixed time sliding mode PI control ant-lion algorithm |