文献类型：会议论文

英文题名：Backstepping Controller Design and Parameter Optimization for Uncertain Nonlinear Chemical Processes

作者：Wu, Tiantian[1];Tian, Yifan[1];Lu, Jingyi[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Smart Mfg Energy Chem Proc, Shanghai 200237, Peoples R China

会议论文集：44th Chinese Control Conference-CCC-Annual

会议日期：JUL 28-30, 2025

会议地点：Chongqing, PEOPLES R CHINA

语种：英文

外文关键词：Backstepping method; Chemical process systems; UKF; GA optimization

摘要：In nonlinear chemical process control, the inherent complex uncertainties make the system behavior difficult to predict, which complicates the design of reliable and efficient control strategies. Considering a class of nonlinear chemical system in the presence of unmeasurable states and unknown parameters, this paper proposes a controller design and optimization method combining the Unscented Kalman Filter(UKF) and Genetic Algorithm(GA). UKF is employed to achieve joint estimation of the unmeasurable states and unknown parameters, and the controller is developed by Backstepping method based on the UKF estimates. Theoretical analysis proves that the designed controller can guarantee that the system is Semi-Globally Uniformly Ultimately Bounded(SGUUB). The parameters of the Backstepping controller are optimized by GA, further reducing resource consumption while maintaining system stability. Finally, a Continuous Stirred Tank Reactor(CSTR) is used as a typical case to comprehensively verify the effectiveness of the proposed method. The simulation results of the CSTR demonstrate that the designed controller ensures the system output quickly reach near the reference value even under uncertain conditions.