Optimization of nonlinear process based on sequential extreme learning machine

Chemical Engineering Science

Volumn 66, Issue 20, 2011, Pages 4702-4710

  Zhang, Yingwei ^a   Zhang, Pengchao ^a  

^a STATE KEY LABORATORY OF SYNTHETICAL AUTOMATION FOR PROCESS INDUSTRIES   (China)

Author keywords

Chemical analysis; Design; KELM; Optimization; Process control; Simulation

Indexed keywords

BATCH PROCESS; BULK POLYMERIZATION; END-PRODUCTS; ERROR FEEDBACK; EXTREME LEARNING MACHINE; INDUSTRIAL PROCESSS; INPUT TRAJECTORY; INPUT VARIABLES; ITERATIVE LEARNING CONTROL; KELM; KERNEL TRICK; MINIMUM COST; NONLINEAR PROCESS; OPTIMAL CONTROLS; OPTIMAL VALUES; OPTIMIZATION PROBLEMS; OUTPUT VARIABLES; PARTICLE SWARM OPTIMIZATION ALGORITHM; SIMULATION; STATE VARIABLES;

BATCH DATA PROCESSING; CHEMICAL ANALYSIS; LEARNING ALGORITHMS; LEARNING SYSTEMS; MAGNESIUM; OPTIMAL SYSTEMS; PARTICLE SWARM OPTIMIZATION (PSO); STYRENE; TWO TERM CONTROL SYSTEMS;

PROCESS CONTROL;

EID: 80051683250     PISSN: 00092509     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ces.2011.06.030     Document Type: Article

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