Journal of South China University of Technology (Natural Science Edition) ›› 2009, Vol. 37 ›› Issue (5): 59-63.

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

Design of Adaptive Control System Based on Linearization Error Model

Jia Li1  Tao Peng-ye1  Qiu Min-sen2   

  1. 1College of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, 2. Faculty of Engineering, National University of Singapore, Singapore 119260
  • Received:2008-04-16 Revised:2008-06-11 Online:2009-05-25 Published:2009-05-25
  • Contact: 贾立（1975-），女，博士，副教授，主要从事复杂非线性系统的建模与控制研究． E-mail:jili@staff．shu．edu．cn
  • About author:贾立（1975-），女，博士，副教授，主要从事复杂非线性系统的建模与控制研究．
  • Supported by:

    上海市国际科技合作基金资助项目（08160705900）;上海市教育委员会科研创新项目（09YZ08）;上海市电站自动化技术重点实验室资助项目

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Abstract:

In order to overcome the nonlinearity and time-varying uncertainty of actual industrial processes, an adaptive control system based on linearization error model is proposed. In this system, first, a composite model consisting a ARX model and a linearization error model based on the neuro-fuzzy system is constructed to describe the nonlinear process. Then, by employing a single-neuron controller and by considering the error between the ARX model output and the system output, as well as the gradient information of the composite model, the controller pa- rameters are adjusted online with high control performance. Simulated results indicate that, as compared with the conventional PID controller, the proposed adaptive controller based on linearization error model is of higher response speed.

Key words: neuro-fuzzy system, adaptive control, linearization error model, single-neuron controller