Author_Institution :
Autom. Dept., Shenyang Aerosp. Univ., Shenyang, China
Abstract :
At present, as a method of establishing mathematical model of the system, the system identification has been widely applied to the automatic control, aviation, space flight, astronomy, medicine, biology, marine ecology and society, economics and many other fields. With the rapid development of science and technology, the status of system identification technique in various disciplines is becoming increasingly important. This paper firstly introduces traditional methods of linear system identification, and then modern methods of nonlinear system identification are introduced briefly Based on the neural network, fuzzy logic, genetic algorithm, swarm intelligence optimization algorithms, auxiliary model identification algorithm, multi-innovation identification algorithm and hierarchical identification algorithm, and finally the author analyses the developing tendency and prospect of system identification.
Keywords :
fuzzy logic; genetic algorithms; identification; linear systems; neural nets; nonlinear systems; swarm intelligence; auxiliary model identification algorithm; fuzzy logic; genetic algorithm; hierarchical identification algorithm; linear system identification; mathematical model; multiinnovation identification algorithm; neural network; nonlinear system identification; swarm intelligence optimization algorithms; system identification method; Algorithm design and analysis; Genetic algorithms; Mathematical model; Neural networks; Nonlinear systems; Optimization; System identification; System identification; auxiliary model identification algorithm; fuzzy logic; genetic algorithm; hierarchical identification algorithm; multi-innovation identification algorithm; neural network; swarm intelligence optimization algorithms;