Cooperative Filtering and Parameter Estimation for Polynomial PDEs using a Mobile Sensor Network
- Resource Type
- Conference
- Authors
- Zhang, Ziqiao; Wu, Wencen; Zhang, Fumin
- Source
- 2022 American Control Conference (ACC) Control Conference (ACC), 2022 American. :982-987 Jun, 2022
- Subject
- Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Parameter estimation
Filtering
Simulation
Partial differential equations
Robot sensing systems
Trajectory
Kalman filters
- Language
- ISSN
- 2378-5861
In this paper, a constrained cooperative Kalman filter is developed to estimate field values and gradients along trajectories of mobile robots collecting measurements. We assume the underlying field is generated by a polynomial partial differential equation with unknown time-varying parameters. A long short-term memory (LSTM) based Kalman filter, is applied for the parameter estimation leveraging the updated state estimates from the constrained cooperative Kalman filter. Convergence for the constrained cooperative Kalman filter has been justified. Simulation results in a 2-dimensional field are provided to validate the proposed method.