Observers for Nonlinear Systems with Unknown Inputs

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  • Cho, Hyeon-Seob (Dept of Digital Broadcast Engineering Chungwoon University) ;
  • Roh, Yong-Gi (Dept of Electrical Engineering Wonkwang University) ;
  • Jang, Sung-Whan (Dept of Electrical Engineering Wonkwang University)
  • 조현섭 (청운대학교디지털방송공학과) ;
  • 노용기 (원광대학교 전기공학과) ;
  • 장성환 (원광대학교 전기공학과)
  • Published : 2006.05.25

Abstract

We consider the problem of constructing observers for nonlinear systems with unknown inputs. It is shown that under some conditions, there exists an observer estimating the states of nonlinear systems with unknown inputs. Nonlinear observer design method using observer error linearization and the design technique of unknown input observer(UIO) for linear systems are used to derive conditions. Some illustrative examples are included. In this paper, a direct controller for nonlinear plants using a neural network is presented. The controller is composed of an approximate controller and a neural network auxiliary controller.The approximate controller gives the rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not put too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system

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