Abstract

Power steering technology help human to control the car. The hydraulic power steering system now tends to be replaced by the electric power steering system (EPS). As the main driver that require precise control. The contribution of this research is to obtain system identification of EPS motor and novelty control strategy to achieve stable control better. Motor control require an appropriate mathematical model and up-down-up down signals of Pseudo Random Binary Signal Sequence (PRBS) were used. The modelling method used was the Numerical Algorithm for Subspace State Space System Identification (N4SID). The quality of the modeling needs to be measured to see whether it was close to the original signal. The validation of the model obtained tested using Variance Accounted For (VAC), Akaike Information Criterion (AIC), and Final Prediction Error (FPE). The best mathematical model was developed on the basis of these three criteria, which is 3rd order model. The control strategy carried out by means of the Ziegler Nichols, Tyreus Luyben and Haugen tuning technique. With these three tuning methods, the control parameters obtained were used for Proprotional-Integral (PI) and Proportional-Integral-Derivative (PID) control. Based on the study, the Haugen control shows the best results of the two other controls, namely with a rise time value of 11,361 ms, overshoot of 6,898%, and steady state at 1.3 s. This show that PI control using the Haugen tuning method able to control the motor well. Robustness tests have also been carried out because the steering system is operated in unpredictable environmental conditions. The control greatly influenced the performance and stability of EPS control in the car's steering system.