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The paper compares the performance of two embedded controllers applied in electrohydraulic steering systems – model predictive controller (MPC) and linear-quadratic  Gaussian  (LQG) controller with  Kalman  filtering for state estimation. Both controllers are designed on the basis of single input multiple output “black box” model obtained via identification approach. The controllers are implemented into industrial logic controller for mobile applications and their workability is experimentally checked with a laboratory model of a steering system for non-road mobile machinery. The results corresponding to investigation of performance of the closed-loop system are presented.

Comparison of Model Predictive Control (MPC) and Linear-Quadratic Gaussian (LQG) Algorithm for Electrohydraulic Steering Control System