OpenFields

A Derivative-Free Extended Information Filtering Approach for Sensorless Control of Nonlinear Systems

The paper examines the problem of sensorless control for nonlinear dynamical systems with the use of derivative-free Extended Information Filtering.

Year of Publication2010

The paper examines the problem of sensorless control for nonlinear dynamical systems with the use of derivative-free Extended Information Filtering. The system is first subject to a linearization transformation and next state estimation is performed by applying the standard Kalman Filter to the linearized model. At a second level, the standard Information Filter is used to fuse the state estimates obtained from derivative-free Kalman Filters running at the local information processing nodes.

This item is categorised as follows

• Subject Collection > Equipment > Design, innovation & technologies

Additional keywords/tags

robotic visual servoingsensorless controlmulti cameras systemextended information filterextended kalman filter