摘要
针对实际工业生产过程中的非线性、时变不确定性,提出了一种基于线性化误差模型的自适应控制系统.首先为非线性过程建立一个由ARX模型与基于神经模糊系统的线性化误差模型组成的合成模型,然后引入单神经元控制器,利用线性ARX模型输出和系统输出值之间的误差,以及被控制过程合成模型的梯度信息,对控制器参数进行在线调节,从而获得较好的控制结果.仿真实验结果表明,与PID控制器相比,基于线性化误差模型的自适应控制器具有更快的响应速度.
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.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2009年第5期59-63,共5页
Journal of South China University of Technology(Natural Science Edition)
基金
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
作者简介
作者简介：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
