State-Space Control Design and Estimation
Use state-space control design methods, such as LQG/LQR and pole-placement algorithms. The toolbox also provides tools for designing observers, including linear and nonlinear Kalman filters.
Categories
- State-Space Control Design
LQG/LQR and pole-placement algorithms
- State Estimation
Design Kalman filters, estimate states during system operation, generate code and deploy to embedded targets
Featured Examples
Estimate States of Nonlinear System with Multiple, Multirate Sensors
Use an Extended Kalman Filter block to estimate the states of a system with multiple sensors that are operating at different sampling rates.
Nonlinear State Estimation of a Degrading Battery System
Estimate the states of a nonlinear system using an unscented Kalman filter in Simulink®.
Detect Replay Attacks in DC Microgrids Using Distributed Watermarking
Detect replay attacks in cyber-physical systems using watermark signals and Kalman filters.
Detect Attack in Cyber-Physical Systems Using Dynamic Watermarking
Detect attacks in cyber-physical systems using dynamic watermark signals.
Detect and Mitigate Attacks in Platooning
Detect and mitigate false data injection attacks in the vehicle-to-vehicle (V2V) communication channel of a platoon.
