Application of Supervisory Predictive Control Based on T-S Model in pH Neutralization Process

Su Zhen Li; Xiang Jie Liu; Gang Yuan

doi:10.4028/www.scientific.net/AMM.511-512.867

Paper Titles

Multi-Sensor Technique-Based Integrated Navigation and Flight Control on Aerial Robot
p.842

An Approach to Command and Control Group Decision-Making Based on Intuitionistic Fuzzy Set
p.851

Analytic Optimization of Implemented Discrete Time for Kalman Filter during Stationary North-Finding
p.857

Dynamic Deployment of Wireless Sensor Networks by an Improved Artificial Bee Colony Algorithm
p.862

Application of Supervisory Predictive Control Based on T-S Model in pH Neutralization Process
p.867

Research on Classification Effectiveness of the Novel Mamdani Fuzzy Classifier
p.871

Delay-Dependent H_∞ Filtering for Neural Networks with Time Delay
p.875

A Novel Infrared Landmark Indoor Positioning Method Based on Improved IMM-UKF
p.880

A Two-Stage Optimization Algorithm of Logistics Transportation Network
p.886

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 511-512Application of Supervisory Predictive Control...

Application of Supervisory Predictive Control Based on T-S Model in pH Neutralization Process

Abstract:

T-S model is linearized at sampling points into the form of linear time-invariant state space , and using supervisory predictive control and muti-step predictive control strategy, which reduces amount of calculation and improves the control performance. Introduction

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 511-512)

Pages:

867-870

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.511-512.867

Citation:

Cite this paper

Online since:

February 2014

Authors:

Su Zhen Li*, Xiang Jie Liu, Gang Yuan

Keywords:

Nonlinear, pH Neutralization Process, Supervisory Predictive Control, T-S Model

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Rawlings J B, Meadows E S, Muske K. Nonlinear Model Predictive Control: A Tutorial and Survey [A]. Proceedings of IFAC ADCHEM[C], Japan, (1994).

DOI: 10.1016/s1474-6670(17)48151-1

Google Scholar

[2] Allgower F, Badgwell T A, Qin S J, Rawlings. J B, Wright. S .J. Nonlinear Predictive Control and Moving Horizon Estimation-an Introductory Overview [A]. In Frank P M(Eds. ), Advances in control: highlights of ECC'99, Berlin, Springer, (1999).

DOI: 10.1007/978-1-4471-0853-5_19

Google Scholar

[3] WU Zhongqiang, XUSifan, YUE Dong. The Terminal Sliding Mode Control for Nonlinear System Based on T-S Model[J]. Control Theory and Applications, 2002. 4, 19(2): 287-290.

Google Scholar

[4] WANG Shuangxin, DONG Yang. Generalized Nonlinear Predictive Controller Based on T-S Fuzzy Model and Small-world Optimization Algorithm[J]. Control and Decision, 2011, 21(5): 21-26.

Google Scholar

[5] LIN Lin, ZHANG Guoxiang, LIU Liying, ZHANG Cuimin, REN Shuyan. Robust H_∞ Fault-tolerant Control for Nonlinear Networked Control System Based on T-S fuzzy model[J]. Journal of Tianjin University of Technology and Education, 2011, 23(1): 67-71.

Google Scholar

[6] Kaveh Hooshmandi, Alireza Yazdizadeh, Mohsen Montazeri. Varying Set-point with Adaptive Predictive Supervisory Controller for Gas Turbine of GILAN Combined Cycle[C]. 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Suntec Convention and Exhibition Center, Singapore, July 14-17, 2009: 280-285.

DOI: 10.1109/aim.2009.5230002

Google Scholar