New Neural Network Inverse Control of Two- Motor Drive System
Two-motor drive system is a multi-variable,nonlinear and strongly coupled system.A new synchronous control strategy for two-motor system is proposed based on radial basis function (RBF) neural network inverse with particle swarm optimization.To enhance the system performance,the particle swarm optimization is adopted to optimize the RBF nerve center,an optimized RBF neural network inverse and a two-motor system is connected in series to form composite pseudo-linear system.This twomotor synchronous system can be decoupled into two independent linear subsystems for speed and tension.Then,the decoupled control is implemented by designing a linear closed-loop adjustor.The experimental results verify that the two-motor synchronous system can be decoupled well for speed and tension based on the proposed neural network inverse system.Also,the proposed system can deal with external disturbances with strong robustness.
Decoupling control inverse system neural network particle swarm optimization
Mei Kang Wenxiang Zhao Jinghua Ji Guohai Liu
School of Electrical and Information Engineering, Jiangsu UniversityZhenjiang 212013, China
国际会议
杭州
英文
1-4
2013-07-07（万方平台首次上网日期，不代表论文的发表时间）