中南大学学报（自然科学版）Issue(10)：3710-3717,8.DOI:10.11817/j.issn.1672-7207.2015.10.022
基于RBF-ARX模型的改进多变量预测控制及应用
An improved multivariable RBF-ARX model-based nonlinear model predictive control approach and application
摘要
Abstract
For a class of smooth nonlinear multivariable systems whose working-points vary with time, a Gaussian radial basis function (RBF) neural networks-based local linearization autoregressive with exogenous (ARX) model was built to describe the system’s global behavior, and an improved nonlinear model predictive control (NMPC) method with adaptive differential effect based on RBF-ARX model identified offline was presented. Difference from conventional NMPC, the differential of errors between model outputs and designed outputs in whole prediction horizon were considered and their weights were adapted by functions of themselves in each optimization process, thus the controller can improve dynamic performance when the steady-state performance is ensured. A case study on a quadrotor for its real attitude control indicates that the proposed method is effective.关键词
RBF-ARX模型/非线性模型预测控制/四旋翼飞行器Key words
RBF-ARX model/nonlinear model predictive control/quadrotor分类
信息技术与安全科学引用本文复制引用
曾小勇,彭辉,吴军..基于RBF-ARX模型的改进多变量预测控制及应用[J].中南大学学报（自然科学版）,2015,(10):3710-3717,8.基金项目
国家自然科学基金资助项目(71271215，71221061)；国家国际科技合作计划项目(2011DFA10440)；湖南省教育厅项目(12C0021)(Projects (71271215,71221061) supported by the National Natural Science Foundation of China （71271215，71221061）
Project (2011DFA10440) supported by the International Science & Technology Cooperation Program of China （2011DFA10440）
Project (12C0021) supported by the Hunan Provincial Education Department) （12C0021）
