A new constrained PSO for fuzzy predictive control of Quadruple-Tank process

Measurement ◽  
2019 ◽  
Vol 136 ◽  
pp. 93-104 ◽  
Author(s):  
Ali Thamallah ◽  
Anis Sakly ◽  
Faouzi M'Sahli
Keyword(s):  
Predictive Control ◽  
Fuzzy Predictive Control

Application of Fuzzy Predictive Control in Grain Drying Coal Burning Hot Air Furnace Temperature Control System

2014 ◽  
Vol 530-531 ◽  
pp. 981-984
Author(s):  
Yao Wu Tang ◽  
Xiang Liu
Keyword(s):  
Control System ◽  
Predictive Control ◽  
Fast Response ◽  
Delay System ◽  
Temperature Control System ◽  
Large Delay ◽  
Blast Stove ◽  
Grain Drying ◽  
Hot Blast ◽  
Fuzzy Predictive Control

Grain drying with chain coalfired hot blast stove for temperature stable and economic operation.Boiler control objects with strong coupling, large delay, large inertia characteristics.Fuzzy control on object for low, fast response and predict advanced features. Design the fuzzy predictive controller for chain coalfired hot blast stove temperature control.The test results show that the fuzzy predictive control system is improved effectively the static precision and dynamic characteristic.Fuzzy predictive control for large delay system has better practicability.

Fuzzy Predictive Control for a Tubular Heat Exchanger System

2013 ◽  
Vol 694-697 ◽  
pp. 2195-2199
Author(s):  
Qiao Ling Ji ◽  
Cong He ◽  
Wei Min Qi ◽  
Jian Kang Zhu
Keyword(s):  
Heat Exchanger ◽  
Predictive Control ◽  
Outlet Temperature ◽  
Adaptive Kalman Filter ◽  
Tubular Heat Exchanger ◽  
Decision Mechanism ◽  
Intelligent Decision ◽  
Control Scheme ◽  
Flow Pressure ◽  
Fuzzy Predictive Control

The paper deals with the problem of controlling the outlet temperature of a tubular heat exchanger system by means of flow pressure. The usual industrial system behavior must precisely be modeled and appropriate control action needs to be obtained based on novel techniques. A new multiple models control strategy using the well-known linear generalized predictive control (LGPC) scheme has been proposed in this paper. Then the best model of the system is accurately identified by an intelligent decision mechanism (IDM) which is organized based on both new recursive weight generator and fuzzy adaptive Kalman filter approaches. Simulations are all done and the results are also compared with those obtained using a nonlinear GPC (NLGPC) approach that is realized based on the Wiener model of the system. The results can verify the validity of the proposed control scheme.

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