Title
Integrated Network-Based Model Predictive Control for Setpoints Compensation in Industrial Processes
Abstract
Complex industrial processes are controlled by the local regulation controllers at the field level, and the setpoints for the regulation are usually made by manual decomposition of the overall economic objective according to the operators' experience. If a precise static process model can be built, real-time optimization (RTO) can be used to generate the setpoints. Nevertheless, since the aforementioned control structure is actually open-loop, the desired economic objective of the whole processes may not be tracked when disturbances exist. Aiming at solving this problem, a novel network based model predictive control method (MPC) for setpoints compensation is proposed in this paper. Firstly, a multivariable proportional integral (PI) controller is designed to perform the local regulation control. Secondly, a stochastic packet dropout model is adopted to characterize the measurement and human-in-the-loop delay effect. Then, a model predictive controller considering the random dropout effect is developed to compensate the setpoints dynamically according to the changing conditions of the processes, such that the prescribed performance objective can be obtained. Finally, a flotation process model is employed to demonstrate the effectiveness of the proposed method.
Year
DOI
Venue
2013
10.1109/TII.2012.2217750
IEEE Trans. Industrial Informatics
Keywords
Field
DocType
rto,optimisation,pi control,network-based control,model predictive control (mpc),setpoints compensation,dropout,integrated network-based model predictive control,setpoint control,mpc,local regulation controllers,human-in-the-loop delay effect,real-time optimization (rto),delays,economic objective,industrial control,multivariable proportional integral controller,multivariable control systems,real-time optimization,complex industrial process,economics,regulation,pi controller,real-time systems,predictive control,indexes,optimization,real time systems,stochastic processes,symmetric matrices
Control theory,Multivariable calculus,Multivariable control systems,Computer science,Control theory,Model predictive control,Network packet,Stochastic process,Control engineering,Symmetric matrix,Operator (computer programming)
Journal
Volume
Issue
ISSN
9
1
1551-3203
Citations 
PageRank 
References 
17
1.06
5
Authors
5
Name
Order
Citations
PageRank
Tianyou Chai12014175.55
Lin Zhao2171.40
Jianbin Qiu32787117.87
Fangzhou Liu412510.67
Jialu Fan534819.01