Chemical Dynamic Parameter Estimation by an Improved TLBO with Quadratic Interpolation

Dynamic parameter estimation plays an important role in the precise modeling of chemical processes.To efficiently handle this problem,we introduce a quadratic interpolation operator to the Teaching-Learning-Based Optimization (TLBO),and TLBO with Quadratic Interpolation (TLBO-QI) is put forward.The quadratic interpolation operator can enhance the local search ability of TLBO.In addition,TLBO-QI is applied to solve three dynamic parameter estimation problems of chemical processes,and compared with TLBO,artificial colony optimization and particle swarm optimization.Computational results show that TLBO-QI can achieve better performance compared with these three algorithms.