: Lyapunov Equation for backward continuous-time Kalman Filter

Click For Summary
SUMMARY

The discussion focuses on the formulation of the Lyapunov equation for a backward continuous-time Kalman filter, specifically in the context of a two-filter smoother. The established steady-state Lyapunov equation for the forward-time system is given as AP + PA' + BB' = 0. The user, Shibdas, seeks clarification on how to derive the Lyapunov equation for the backward-time filter, which modifies the system to -dx/dt = Fx + Gv. It is concluded that the augmented system must incorporate both the backward filter and the forward system equations to accurately evaluate the error-covariance using the Lyapunov equation.

PREREQUISITES
  • Understanding of continuous-time Kalman filters
  • Familiarity with Lyapunov equations
  • Knowledge of Riccati equations in control theory
  • Basic concepts of state-space representation
NEXT STEPS
  • Research the derivation of the Lyapunov equation for backward Kalman filters
  • Study the application of Riccati equations in backward filtering
  • Explore the implications of augmented systems in control theory
  • Learn about the relationship between state-covariance matrices and error-covariance in Kalman filtering
USEFUL FOR

Researchers, control engineers, and students working on advanced Kalman filtering techniques and those interested in the mathematical foundations of state estimation and error analysis.

shibdas
Messages
2
Reaction score
0
URGENT: Lyapunov Equation for backward continuous-time Kalman Filter

Hi,

Consider a continuous Kalman filter running backward in time as desired in a "two-filter" smoother. What would be the form of Lyapunov equation for this backward-time filter?

Given a system: dx/dt = Fx + Gv, and, say, a forward Kalman filter: dX/dt = CX + Dx + Ew (where X is the filtered esimate of the state x, and v, w are white noises), the augmented system would be: d/dt [x X]' = A [x X]' + B [v w]'

Then, the (steady-state) Lyapunov equation for the augmented (forward-time) system is: AP + PA' + BB' = 0.

In backward-time, the system modifies to: - dx/dt = Fx + Gv, and accordingly the (backward) Kalman filter may be obtained using standard Riccati equation approach. How would the augmented system be obtained to be used for Lyapunov equation? What is the form of the Lyapunov equation in this case, if different from the forward-case mentioned earlier? I need to be able to use Lyapunov equation to derive the state-covariance matrix and the error-covariance from that.

Thanks in advance,
Shibdas.
 
Engineering news on Phys.org


shibdas said:
Hi,

Consider a continuous Kalman filter running backward in time as desired in a "two-filter" smoother. What would be the form of Lyapunov equation for this backward-time filter?

Given a system: dx/dt = Fx + Gv, and, say, a forward Kalman filter: dX/dt = CX + Dx + Ew (where X is the filtered esimate of the state x, and v, w are white noises), the augmented system would be: d/dt [x X]' = A [x X]' + B [v w]'

Then, the (steady-state) Lyapunov equation for the augmented (forward-time) system is: AP + PA' + BB' = 0.

In backward-time, the system modifies to: - dx/dt = Fx + Gv, and accordingly the (backward) Kalman filter may be obtained using standard Riccati equation approach. How would the augmented system be obtained to be used for Lyapunov equation? What is the form of the Lyapunov equation in this case, if different from the forward-case mentioned earlier? I need to be able to use Lyapunov equation to derive the state-covariance matrix and the error-covariance from that.

Thanks in advance,
Shibdas.

Welcome to the PF.

Can you give us the context of your question? Why is it urgent? Is it for schoolwork?
 


Yes, this is for my research work in my school. It is urgent because I need to present my work soon.

Note that I know that the error-covariance for the backward filter is simply the solution of the steady-state Riccati equation used to obtain the backward Kalman filter. But, I need to use Lyapunov equation (for the augmented system) to evaluate it and demonstrate that the two errors are the same.

It appears to me that the correct answer may be obtained ONLY if the augmented system considers, alongwith the backward filter equation, the forward system equation: dx/dt = Fx + Gv, rather than the backward system equation: - dx/dt = Fx + Gv (which is strange).

Thanks,
Shibdas.
 

Similar threads

Replies
9
Views
7K
Replies
2
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
Replies
1
Views
1K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 7 ·
Replies
7
Views
22K
  • · Replies 1 ·
Replies
1
Views
4K
  • · Replies 11 ·
Replies
11
Views
4K