Earticle

초록

영어

The multi-sensor information fusion predictive control algorithm for discrete-time linear time-invariant stochastic control system with random time-delay observations is presented in this paper. The algorithm applies the fusion steady-state Kalman filter to the predictive control. It avoids the complex Diophantine equation and it can obviously reduce the computational burden. The algorithm can deal with the multi-sensor discrete-time linear time-invariant stochastic controllable system based on the linear minimum variance optimal information fusion criterion. The fusion method includes the centralized fusion, global optimality weighted measurement fusion. And the two fusion method is completely functionally equivalence. Compared with the single sensor case, the accuracy of the fused filter is greatly improved. A simulation example of the target tracking controllable system with two sensors shows its effectiveness and correctness.

목차

Abstract
 1. Introduction
 2. Problem Formulation
 3. Local Steady-State Kalman Filter
 4. Fusion Kalman Filter
 5. Predictive Control Algorithm Base on Steady-State Kalman Filter
 6. Simulation Example
 7. Conclusion
 Acknowledgement
 References

키워드

저자

• Yun Li [ School of Computer and Information Engineering Harbin University of Commerce HeiLongjiang, Harbin, 150001, China, Electronic Engineering Institute Heilongjiang University Heilongjiang, Harbin, 150080, China ]
• Ming Zhao [ School of Computer and Information Engineering Harbin University of Commerce HeiLongjiang, Harbin, 150001, China ]
• Gang Hao [ Electronic Engineering Institute Heilongjiang University Heilongjiang, Harbin, 150080, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605