A Joint State and Fault Estimation Scheme for State-Saturated System with Energy Harvesting Sensors

Area of Science:

• Control Systems Engineering
• Signal Processing
• Estimation Theory

Background:

• State-saturated systems are common in real-world applications.
• Energy harvesting sensors introduce challenges like measurement loss and variable power availability.
• Time delays are inherent in many networked and distributed systems.

Purpose of the Study:

• To design a joint state and fault estimator for delayed, state-saturated systems with energy harvesting sensors.
• To ensure the estimation error covariance is bounded.
• To develop an estimator gain that accounts for energy harvesting, saturation, and delays.

Main Methods:

• Utilizing matrix difference equations to derive an upper bound for estimation error covariance.
• Parameterizing the estimator gain to minimize the derived upper bound.
• Analyzing the boundedness of the estimation error in the mean-squared sense for performance evaluation.

Main Results:

• A novel joint state and fault estimation scheme is proposed.
• The estimator gain is optimized to handle system complexities.
• The performance evaluation demonstrates the boundedness of the estimation error.

Conclusions:

• The proposed estimation scheme is feasible for systems with energy harvesting, state saturation, and time delays.
• The method effectively manages measurement loss probability and ensures bounded estimation error.
• Experimental validation confirms the practical applicability of the developed estimator.