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中南大学学报(自然科学版)

Journal of Central South University

第46卷    第10期    总第254期    2015年10月

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文章编号:1672-7207(2015)10-3710-08
基于RBF-ARX模型的改进多变量预测控制及应用
曾小勇1, 2,彭辉1,吴军1

(1. 中南大学 信息科学与工程学院,湖南 长沙,410083;
2. 长沙理工大学 电气与信息工程学院,湖南 长沙,410076
)

摘 要: 针对一类工作点时变的光滑非线性多变量被控对象,采用离线辨识的RBF-ARX模型描述系统的全局非线性动态特性,并在此基础上提出一种具有自适应微分作用的非线性模型预测控制方法。该方法将整个预测时域内模型输出和期望输出的偏差变化率考虑到优化目标中,利用与偏差变化率有关的函数动态修改该优化项的权重,从而能在保证控制器稳态性能的情况下有效地改善系统的动态性能。最后利用该方法对四旋翼飞行器实验装置进行了实际的姿态控制,控制效果验证该方法的有效性。

 

关键字: RBF-ARX模型;非线性模型预测控制;四旋翼飞行器

An improved multivariable RBF-ARX model-based nonlinear model predictive control approach and application
ZENG Xiaoyong1, 2, PENG Hui1, WU Jun1

1. School of Information Science and Engineering, Central South University, Changsha 410083, China;
2. School of Electrical and Information Engineering,
Changsha University of Science and Technology, Changsha 410076, China

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.

 

Key words: RBF-ARX model; nonlinear model predictive control; quadrotor

中南大学学报(自然科学版)
  ISSN 1672-7207
CN 43-1426/N
ZDXZAC
中南大学学报(英文版)
  ISSN 2095-2899
CN 43-1516/TB
JCSTFT
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