An event-triggered extend state observer is developed for dynamic positioning vessels in [1], and an event-triggering condition is developed by using the position errors. It is suitable for dynamic positioning task aimed at stabilizing to a stationary position. In this paper, we aim to solve the state and uncertainty estimation problem for unmanned surface vehicles in a moving task. Specifically, a prediction-based event-triggered extended state observer is developed for estimating the uncertainties using intermittent communication. A prediction mechanism is used to predict the current position of the vehicle by using the last transmitting position-yaw measurements, and an event-triggering condition is developed using the prediction errors. The main feature of this paper lies in that the communication times are drastically reduced regardless of fast variation of vehicle position. The input-to-state stability of the estimation errors is proven. Comparison studies are given to demonstrate the effectiveness of the proposed prediction-based event-triggered extended state observer.
Prediction-Based Event-triggered Extended State Observers Design for Unmanned Surface Vehicles
2021-07-01
1434514 byte
Conference paper
Electronic Resource
English
Event-Triggered Reliable State Estimation for Networked Unmanned Surface Vehicles with Sensor Faults
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|Event-Triggered Extended State Observer
Springer Verlag | 2021
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