文献类型：会议论文

英文题名：Adaptive control of continuous time-varying bioprocesses using recursive kernel learning controller with polynomial form

作者：Chen, Kun[1]; Liu, Yi[2]

机构：[1] Department of Electrical and Information Engineering, Shaoxing University, Shaoxing 312000, China; [2] Engineering Research Center of Process Equipment and Remanufacturing, Ministry of Education, Zhejiang University of Technology, Hangzhou 310032, Zhejiang, China

会议论文集：13th IFAC Symposium on Large Scale Complex Systems: Theory and Applications, LSS 2013 - Proceedings

会议日期：July 7, 2013 - July 10, 2013

会议地点：Shanghai, China

语种：英文

外文关键词：Continuous time systems - Controllers - Large scale systems - Learning algorithms - Learning systems - Polynomials - Proportional control systems - Time varying control systems - Two term control systems

外文摘要：Many bioprocesses are difficult to control due to their highly nonlinear and time-varying characteristics. To design simple and suitable controllers for these processes, a nonlinear predictive controller using sparse kernel learning with a polynomial kernel form is designed. First, the nonlinear time-varying processes can be identified using the recursive kernel learning method. The online kernel identification model can be efficiently updated, with nodes increasing and decreasing, via recursive learning algorithms. Consequently, the proposed polynomial kernel learning-based controller can restrict its complexity, and trace the time-varying characteristics of a nonlinear process adaptively to achieve better performance. The obtained results on a continuous bioreactor with time-varying parameters show that the proposed controller is superior to the traditional proportional-integral-derivative (PID) controller and other kernel controllers with an offline model without online updating. ? IFAC.