高技术通讯2011，Vol.21Issue(9)：967-973,7.DOI:10.3772/j.issn.1002-0470.2011.09.014
基于Bloch量子遗传算法的倒立摆模糊控制器优化设计
Fuzzy controller optimization for inverted pendulum systems based on the Bloch quantum genetic algorithm
摘要
Abstract
To solve the optimization design of fuzzy controllers for inverted pendulums, an novel design optimization approach based on the Bloch quantum genetic algorithm ( BQGA) is proposed. This approach regards the three Bloch coordinates of each qubit as paratactic genes. Each chromosome contains three gene chains, and each of the gene chains represents an optimization solution that is a group of controller parameters, which can accelerate the convergence process for the same number of chromosomes as the common quantum genetic algorithm (CQGA). With the fuzzy neural network controller (FNNC) for a single inverted pendulum being an example, the experiment was perfomed and the control effect was discussed in detail based on two initial states. The experimental results demonstrate that the BQGA-based design is obviously superior to the CQGA-based design, and the FNNC designed using the BQGA-based approach is obviously superior to the LQR controller when the systematical parameter changes.关键词
量子遗传算法(QGA)/模糊控制器/倒立摆控制/参数优化/算法设计Key words
quantum genetic algorithm (QGA)/fuzzy controller/inverted pendulum control/parameter optimization /algorithm design引用本文复制引用
李盼池,宋考平,杨二龙..基于Bloch量子遗传算法的倒立摆模糊控制器优化设计[J].高技术通讯,2011,21(9):967-973,7.基金项目
国家自然科学基金(61170132),国家博士后基金(20090460864,201003405),黑龙江省博士后基金(LBH-Z09289)和黑龙江省教育厅科学技术基金(11551015,11551017)资助项目. （61170132）
