Nonlinear Systems Identification and Control via Dynamic Multitime Scales Neural Networks

作者：Fu, Zhi-Jun^*; Xie, Wen-Fang; Han, Xuan; Luo, Wei-Dong

来源：IEEE Transactions on Neural Networks and Learning Systems, 2013, 24(11): 1814-1823.

DOI：10.1109/TNNLS.2013.2265604

• Dynamic multitime scale neural networks
• neural network controller
• nonlinear systems
• online identification

This paper deals with the adaptive nonlinear identification and trajectory tracking via dynamic multilayer neural network (NN) with different timescales. Two NN identifiers are proposed for nonlinear systems identification via dynamic NNs with different timescales including both fast and slow phenomenon. The first NN identifier uses the output signals from the actual system for the system identification. In the second NN identifier, all the output signals from nonlinear system are replaced with the state variables of the NNs. The online identification algorithms for both NN identifier parameters are proposed using Lyapunov function and singularly perturbed techniques. With the identified NN models, two indirect adaptive NN controllers for the nonlinear systems containing slow and fast dynamic processes are developed. For both developed adaptive NN controllers, the trajectory errors are analyzed and the stability of the systems is proved. Simulation results show that the controller based on the second identifier has better performance than that of the first identifier.

• 出版日期2013-11
• 单位浙江工业大学; 北京科技大学