Journal of Systems Engineering and Electronics

• CONTROL THEORY AND APPLICATION • Previous Articles     Next Articles

Model algorithm control using neural networks for input delayed nonlinear control system

Yuanliang Zhang1 and Kil To Chong2,*     

  1. 1. School of Mechanical Engineering, Huaihai Institute of Technology, Lianyungang 222005, China;
    2. School of Electronics and Information, Chonbuk National University, Jeonju 560756, South Korea
  • Online:2015-02-13 Published:2010-01-03


The performance of the model algorithm control method is partially based on the accuracy of the system’s model. It is difficult to obtain a good model of a nonlinear system, especially when the nonlinearity is high. Neural networks have the ability to “learn” the characteristics of a system through nonlinear mapping to represent nonlinear functions as well as their inverse functions. This paper presents a model algorithm control method using neural networks for nonlinear time delay systems. Two neural networks are used in the control scheme. One neural network is trained as the model of the nonlinear time delay system, and the other one produces the control inputs. The neural networks are combined with the model algorithm control method to control the nonlinear time delay systems. Three examples are used to illustrate the proposed control method. The simulation results show that the proposed control method has a good control performance for nonlinear time delay systems.

Key words: model algorithm control, neural network, nonlinear system, time delay