Parameter estimation for nonlinear system using intelligent algorithm
Xiaoping Xu1, Feng Wang2, Fucai Qian3
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(12C) 367-371
1 School of Sciences, Xi’an University of Technology, No.58 Yanxiang Road, Xi’an, China
2 School of Mathematics and Statistics, Xi’an Jiaotong University, No.28 Xianning Road, Xi’an, China
3 School of Automation and Information Engineering, Xi’an University of Technology, No.5 Jinhua Road, Xi’an, China
Mathematical models are the basis of all control problems. The movement law of things described by equations is the mathematical model. The traditional paradigm of system identification employs prior information on system structures and environments and input/output observation data to derive system models. Accordingly, system identification becomes one of the current active subjects in engineering problems. It is well known that nonlinear systems widely exist in people’s production and life. Consequently, in this paper, a parameter estimation method of nonlinear system is put forward based on an improved artificial fish swarm algorithm. Its basic idea is as follows. Firstly, the parameter estimation problems of nonlinear systems are changed into a nonlinear function optimization problem over parameter space. Then, the estimates of the system parameters are obtained based on an improved artificial fish swarm algorithm. Finally, in simulation, compared with other algorithms, the simulation results indicated that the presented method is rational and effective.