A linear quadratic tracking control strategy based on fuzzy for electric power steering systems

Stability and steering comfort are improved using an Electric Power Steering (EPS) system instead of a traditional Hydraulic Power Steering (HPS) system. A new control algorithm is proposed in this work to control automotive EPS systems. The proposed algorithm solves two main existing problems: eliminating the influence of systematic errors and ensuring tracking for all state variables instead of just a single object. This algorithm is formed based on a combination of Fuzzy and Linear Quadratic Tracking control techniques, so it is called FLQT. The proposed fuzzy technique has two inputs, angle error, and rate error, which are used to correct the input signal of the LQT technique and reduce systematic error. Simulation results are obtained from specific cases corresponding to two types of driver torques. The article shows that when the FLQT algorithm controls the system, the Root Mean Square (RMS) error does not go over 0.021% (in the first case) or 0.057% (in the second case). However, conventional LQT and Proportional-Integral-Derivative (PID) techniques can increase the RMS error to 18.809% and 42.543%, respectively. System stability and adaptability are guaranteed even when vehicle speed and driver torque change.