State Estimation for Hybrid Systems

Our group develops a set of state estimation algorithms for a Stochastic Hybrid System (SHS) based on the Interacting Multiple Model (IMM) Algorithm.

  • State estimation for a SHS
    • Discrete-time Stochastic Linear Hybrid System (SLHS)
      • SLHS: Residual-Mean IMM (RMIMM) Algorithm [1]
      • SLHS with State-Dependent-Transition: State-Dependent-Transition Hybrid Estimation (SDTHE) Algorithm [2,3]
      • SLHS with Unknown Fault Input: Unknown Fault Input Hybrid Estimation (UFIHE) Algorithm
      • SLHS with State Constraints: Constrained Innovation Hybrid Estimator (CIHE)
    • Continuous-time SHS [4]
  • Analysis of the IMM Algorithm
    • Performance of the IMM Algorithm [5]
    • Stability of the IMM Algorithm [6]

Related Publications

  1. I. Hwang, H. Balakrishnan, and C. Tomlin, “State Estimation for Hybrid Systems: Applications to Aircraft Tracking,” IEE Proceedings of Control Theory and Applications, Vol. 153(5): 556-566, September 2006
  2. C.-E. Seah and I. Hwang, “State Estimation for Stochastic Linear Hybrid Systems with Continuous-State-Dependent Transitions: An IMM Approach,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 45(1), January 2009
  3. C.-E. Seah and I. Hwang, “Stochastic Linear Hybrid Systems: Model, Estimation, and Application to Aircraft Tracking,” IEEE Transactions on Control Systems Technology, Vol. 17(3), May 2009
  4. W. Liu and I. Hwang, “On Hybrid State Estimation for Stochastic Hybrid Systems,” IEEE Transactions on Automatic Control, Vol.59(10), pp.2615-2628, October 2014
  5. C.-E. Seah and I. Hwang, “Algorithm for Performance Analysis of the IMM Algorithm” IEEE Transactions on Aerospace and Electronic Systems, Vol. 47(2), p1114- 1124, April 2011
  6. I. Hwang, C.-E. Seah, and S. Lee, "A Study on Stability Analysis of the Interacting Multiple Model Algorithm," IEEE Transactions on Automatic Control, Vol.59(10), April 25 2016, doi: 10.1109/TAC.2014.2322152