State Estimation under Multi-Rate Sensing: IEEE ACCESS 2023

MATLAB implementation of the multirate state observer design method.

MATLAB implementation of the multirate state observer design method presented in the IEEE ACCESS paper "State Observer Under Multi-Rate Sensing Environment and Its Design Using l2-Induced Norm" (DOI:https://doi.org/10.1109/ACCESS.2023.3249187).

This toolkit enables state estimation for systems with multiple outputs sampled at different rates—a common scenario in modern networked control systems, sensor networks, and multi-sensor fusion applications.

Key Features:

- State observer design for asynchronous multi-rate measurements

- l2-induced norm based performance optimization

- Handles outputs with different sampling intervals (e.g., y1 every 2 steps, y2 every 6 steps)

- Comprehensive visualization of:

- True vs. estimated states

- Estimation errors for each state

- Multi-rate output measurements

- Input signals

- Numerical example from the paper included for validation

- Easily adaptable to custom system models and sampling patterns

Technical Highlights:

- Rigorous observer design based on lifted system representation

- Guaranteed estimation performance via l2-induced norm framework

- Robust to measurement timing variations

Perfect for:

- Networked control systems research

- Multi-sensor fusion applications

- Aperiodic/event-triggered sensing systems

- Industrial IoT and cyber-physical systems

Reference: H. Okajima, et al., "State Observer Under Multi-Rate Sensing Environment and Its Design Using l2-Induced Norm," IEEE ACCESS, 2023. DOI: 10.1109/ACCESS.2023.3249187

Compatible with MATLAB R2016b and later. Requires Control System Toolbox.

State Observer Under Multi-Rate Sensing Environment and Its Design Using l2-Induced Norm | IEEE Journals & Magazine | IEEE Xplore