Robust filtering in discrete stochastic systems with jump parameters and interval uncertainty

Key Points

• The robust filtering algorithm effectively estimates states in the presence of interval uncertainty and jump parameters.
• Using the Kalman filtering schemes, the algorithm accommodates variability through independent uniform random variables.
• This method addresses filtering challenges in discrete stochastic systems versus fixed parameter approaches, highlighting its adaptability.
• Overall, the approach demonstrates the utility of probabilistic models for better performance in complex systems with variability.