Title :
Research of an improved particle filter algorithm
Author :
Yong-Wei Li;Ming-Xing Chen
Author_Institution :
College of electrical engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
fDate :
7/1/2015 12:00:00 AM
Abstract :
Aiming at the problem of the low accuracy, which is caused by the scarcity of particles and the local optimization in particle filter, this paper puts forward an improved particle filter based on particle swarm optimization to overcome the shortcomings of the scarcity of particles and the local optimization in particle filter. At last, the improved particle filter algorithm is applied to the process of the synthetic ammonia, aiming at the optimization of the complex industrial process which contains the characteristics of nonlinearity, non-Gaussian, large delay, strong coupling and it is difficult to establish a control model online, thus it can make that the complex industrial process reflects the true state more accurately. The simulation results show that it improves the precision of the algorithm when compared with the simple particle filter algorithm, and in the complex industrial process of synthetic ammonia the algorithm has the practical application value and also provides an effective way for the optimization control of a class of complex industrial process.
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2015 International Conference on
DOI :
10.1109/ICMLC.2015.7340646