A tune sliding control algorithm for angle following of electric motor steer‐by‐wire system

Abstract The sliding mode control has to design a sliding manifold for manipulating the system motion in engineering practice, making system asymptotic stability paramount. This is particularly challenging for using variable sliding manifold parameters to formulate the sliding manifold for fast convergence and precise control. While much of the research on sliding mode control has focused on constant sliding manifold parameters, comparatively little is known about the variable approach of the sliding manifold parameters. Therefore, sliding manifold parameters are treated as variables and are computed by a parameter tuning algorithm. Regarding the parameter tuning algorithm, its input is the sliding mode control law with variable sliding manifold parameters, and its output is the computed sliding manifold parameters that will be transmitted back to the sliding mode control law. Through tuning the sliding manifold parameters by an optimal method of lowest cost with the measuring value and model computing value of system states based on the historical information, the difference between the nominal model and the real system will be removed. Here we discuss a series of studies on the algorithm of tune sliding control that, collectively, develop an application of how the tune sliding controller steers the front wheels of the full self‐driving vehicle. The designed approach has been tested in a steering test vehicle to realize a good angle tracking performance of the electric motor steer‐by‐wire system.