A Networked Predictive Control Algorithm Based on T-S Fuzzy Model

Author

Jia Rong ; Chen Zhichu ; Liu Bin

Author_Institution

Sch. of Electr. & Inf. Eng., Hubei Univ. of Automotive Technol., Shiyan, China

fYear

2013

fDate

21-23 June 2013

Firstpage

1501

Lastpage

1504

Abstract

Network time-delay is usually uncertain or random, packet loss and timing disorder also can be summed up in a certain degree of time-delay. In this paper, we focused on networked control systems (NCS) with bounded uncertain time delays. Utilizing extended TakagiSugeno (T-S) fuzzy models, the characteristics of such a system is better expressed. Based on these fuzzy models, a fuzzy generalized predictive control algorithm based on Markov uncertain delay and subspace Toeplitz equations is proposed. By introducing subspace Toeplitz prediction equation, the overall optimal control input is obtained by fuzzy "blending" of all subspaces control law. Finally, a simulation example was given.

Keywords

Toeplitz matrices; delays; distributed parameter systems; fuzzy control; fuzzy systems; networked control systems; optimal control; predictive control; stochastic systems; uncertain systems; Markov uncertain delay; NCS; T-S fuzzy model; Takagi-Sugeno fuzzy models; bounded uncertain time delays; fuzzy blending; fuzzy generalized predictive control algorithm; network time-delay; networked control systems; networked predictive control algorithm; overall optimal control input; packet loss; subspace Toeplitz prediction equation; timing disorder; Delay effects; Delays; Equations; Markov processes; Mathematical model; Predictive control; Predictive models; Networked Control Systems; Predictive Control; Takagi-Sugeno (T-S) models; Toeplitz Equations; Uncertain Time Delays;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on

Conference_Location

Shiyang

Type

conf

DOI

10.1109/ICCIS.2013.395

Filename

6643313