System Identification of Farm Vehicles
using Carrier Phase Differential GPS

Gabriel Elkaim, Michael O'Connor,
Thomas Bell, and Bradford Parkinson

Department of Aeronautics and Astronautics
Stanford University

Presented September 1996 at ION GPS-96, Kansas City, Missouri

ABSTRACT

The automatic operation of farm vehicles can have great benefits both in farm productivity and hazardous or impossible operations. Automatic control offers many potential improvements over human control; however, previous efforts have failed largely due to sensor limita-tions. Carrier Phase Differential GPS (CDGPS) is an enabling technology that provides a high-bandwidth, low-noise measurement of multiple vehicle states. System identification techniques can then be used to generate a mathematical model for automatic control system design and implementation.

In this work, previous controls research on a large tractor test bed is extended to demonstrate two different methods of system identification. Using a priori knowledge of the tractor dynamics, an extended Kalman filter is imple-mented and demonstrates model parameter identification. A Linear Quadratic Regulator (LQR) controller, based on these parameters, performs closed loop line tracking with a demonstrated error of better than 1.8 cm standard deviation.

The same data is used with the Observer/Kalman Filter Identification (OKID) method, which assumes no a priori information about the system dynamics. It is shown that the estimator/controller designed with this system demon-strates equivalent experimental performance. The OKID methodology differs from the extended Kalman filter by utilizing solely the input and output streams to determine the structure and order of the plant model.

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