Event-Triggered State and Disturbance Estimation for Lipschitz Nonlinear Systems With Unknown Time-Varying Delays.

Area of Science:

• Control Systems Engineering
• Nonlinear System Analysis
• Estimation Theory

Background:

• Estimating system states and disturbances is crucial for control and monitoring.
• Existing methods often require continuous data, straining communication resources.
• Unknown time-varying delays complicate state estimation in nonlinear systems.

Purpose of the Study:

• To develop an event-triggered state observer for simultaneous state and disturbance estimation.
• To address the challenge of unknown time-varying delays in Lipschitz nonlinear systems.
• To reduce communication load compared to traditional continuous-time observers.

Main Methods:

• Proposal of a novel event-triggered state observer.
• Establishment of a sufficient condition for observer existence.
• Utilization of algebraic transformations and matrix inequalities (Cauchy matrix, Schur complement lemma) for parameter synthesis.
• Formulation of a convex optimization problem for deriving observer parameters and disturbance attenuation levels.

Main Results:

• The proposed observer enables robust simultaneous state and disturbance estimation using event-triggered output information.
• The method effectively handles unknown time-varying delays.
• Reduced communication stress is achieved without significant performance degradation.
• A systematic approach for parameter synthesis via convex optimization is presented.

Conclusions:

• The developed event-triggered observer offers an efficient solution for state and disturbance estimation in nonlinear systems with delays.
• This approach enhances practical applicability by reducing communication requirements.
• The method's validity is confirmed through numerical examples.