Dynamic event-triggered prescribed-time observer via parametric Lyapunov equations.

Area of Science:

• Control Systems Engineering
• Observer Design
• Event-Triggered Systems

Background:

• Traditional prescribed-time observers (PTOs) require continuous data, increasing communication load.
• Existing event-triggered methods often struggle to guarantee prescribed-time convergence.
• High communication costs are a significant challenge in real-time state estimation.

Purpose of the Study:

• To develop a dynamic event-triggered prescribed-time observer (DETPTO) for linear systems.
• To achieve fast state estimation within a defined time T.
• To reduce communication overhead by updating measurements only when necessary.

Main Methods:

• Utilizing a novel dynamic event-triggered mechanism (DETM) with bounded triggering conditions.
• Employing a parametric Lyapunov equation (PLE) for observer design.
• Integrating estimation and measurement errors into the DETM to optimize updates.

Main Results:

• The proposed DETPTO guarantees state estimation within a prescribed time T.
• The DETM effectively reduces measurement output updates, lowering communication costs.
• Zeno behavior is successfully avoided, ensuring practical implementation.

Conclusions:

• The developed DETPTO offers an efficient solution for fast state estimation in linear systems.
• The novel DETM balances estimation speed with communication efficiency.
• Numerical simulations confirm the effectiveness and practical applicability of the proposed observer.