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Matrix, Control and Robotics

Matrix, Control and Robotics

Category Archives: Linear Systems

Variations of Kalman filter

09 Friday May 2014

Posted by junkailu in Kalman Filter, Linear Systems

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1. Colored process and output noises

2. Non-zero mean process and output noises

3. No output noises

Two approaches of checking linear system’s detectability

08 Thursday May 2014

Posted by junkailu in Linear Systems

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Approach I:

Use Kalman Canonical Form Decomposition:

Approach II:

Only check if the modes corresponding to unstable eigenvalues are observable or not. (Since stable modes can always tend to zero asymptotically, we only need to check if the observability of the unstable modes).

  • Find out eigenvalues of transition matrix A \in \mathbb{R}^{n\times n}
  • If all eigenvalues are Hurwitz (continuous-time system) or Schur (discrete-time system), then (C,A) is detectable
  • If there are unstable eigenvalues, say, \lambda, then check

\text{rank}\begin{bmatrix} A-\lambda I\\C\end{bmatrix}

is equal to n or not.

Categories

  • Hardware
  • Kalman Filter
  • LaTeX
  • Linear Systems
  • MATLAB
  • Robotics
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