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作 者:刘宝[1] 叶会会 蔡梦迪 LIU Bao;YE Huihui;CAI Mengdi(College of Information and Control Engineering, China University of Petroleum, Qingdao 266580, China;Qingdao Xingyi Electronic Equipment Co. Ltd., 41st Institute of CETC, Qingdao 266510, China)
机构地区:[1]中国石油大学(华东)信息与控制工程学院,山东青岛266580 [2]中国电子科技集团第四十一研究所青岛兴仪设备有限责任公司,山东青岛266510
出 处:《中南大学学报(自然科学版)》2019年第4期881-891,共11页Journal of Central South University:Science and Technology
基 金:国家自然科学基金资助项目(60534020;60775052);山东省优秀中青年科学家科研奖励基金资助项目(BS2010DX038)~~
摘 要:为进一步解决常规模糊控制算法存在的控制器参数不能在线调整、稳态精度较低等问题,提出一种基于免疫系统调节机制的参数自整定模糊控制算法。该算法在动态调节阶段借鉴生物免疫系统调的T细胞反馈调节机制来整定控制器参数,以获得较优的控制系统动态性能;稳态调节阶段利用免疫系统抗原提呈原理,将控制偏差视为抗原并进行非线性处理,同时微调控制器参数以提高模糊控制器的灵敏度,从而克服常规模糊控制器稳态精度不高的缺陷。为检验免疫模糊自整定控制算法的控制效果,将改进后的算法应用于生物反应器的非线性温度控制对象。研究结果表明:相比于常规模糊控制算法和PID算法,免疫模糊自整定控制算法具有较好的控制效果和较强的抗干扰能力。In order to solve the problem that the controller parameters of conventional fuzzy control algorithm cannot be adjusted online and the steady-state accuracy was not high enough, a fuzzy self-tuning control algorithm based on immune regulation mechanism was proposed. In the stage of dynamic adjustment, the T cell regulation mechanism of biological immune system was used to adjust the controller parameters to achieve better dynamic performance of the control system. In the stage of steady regulation, based on the principle of antigen presentation, the input deviation of controller was processed nonlinearly, and the controller parameter was adjusted at the same time to improve its sensitivity, so as to overcome the defect of steady accuracy of conventional fuzzy controller. At last, the improved control algorithm was applied to the nonlinear temperature object of a bioreactor in order to testify its control performance. The results show that compared with the conventional fuzzy control algorithm and PID algorithm, the improved self-tuning fuzzy control algorithm based on immune regulation can achieve better control effect and stronger anti-interference ability.
分 类 号:TP18[自动化与计算机技术—控制理论与控制工程]
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