CONSTRAINED PI TRACKING CONTROL FOR THE OUTPUT PDFS BASED ON T-S FUZZY MODEL

被引：0
|
作者：
Yi, Yang [1 ]
Guo, Lei [1 ,2 ]
机构：
[1] Southeast Univ, Res Inst Automat, Nanjing 210096, Peoples R China
[2] Beijing Univ Aeronaut & Astronaut, Inst Instrumentat & Optoelect Engn, Beijing 100083, Peoples R China
来源：
INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL | 2009年 / 5卷 / 02期
基金：
美国国家科学基金会;
关键词：
Probability density function; Non-Gaussian stochastic systems; PI controller; B-spline neural network; T-S Fuzzy model; Peak-to-peak performance; PROBABILITY DENSITY-FUNCTIONS; STOCHASTIC-SYSTEMS; CONTROL DESIGN; NONLINEAR-SYSTEMS; FEEDBACK-CONTROL; TIME-DELAYS; STABILITY;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a new proportional-integral (PI) tracking control strategy for general non-Gaussian stochastic systems based on neural network approximation and T-S fuzzy model identification. The objective is to control the conditional probability density function (PDF) of system output to follow a desired PDF. Following the B-spline approximation on the measured output PDFs, the PDF tracking is transformed to a constrained dynamic tracking control problem for weighting vectors. Different from previous related works, the time delay T-S fuzzy model is applied to identify the nonlinear weighting dynamics. Meanwhile, art improved PI controller design procedure based on LMIs is proposed which can guarantee the required tracking convergence. Furthermore, the robust peak-to-peak measure is applied to optimize the tracking performance.
引用
收藏
页码：349 / 358
页数：10
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