Adaptive Lateral Motion Control with Hybrid Approach

The complexity of controlling robotic system is primarily because of nonlinearity in actuation system and uncertainties in sensing of the surrounding environment. The linear feedback control mechanism is not sufficient to control vehicle maneuver with precision, thus it summons research of adaptive control approach. An adaptive control strategy is most often deployed to control system with unknown plant model or a system with minimal information. The objective of the proposed hybrid control strategy is to deal with non-linearity in the actuation system with minimum tuning effort. An iterative back-stepping mechanism is used to design model reference adaptive control to aid vehicle maneuver. The aim of this paper is to analysis the stability of non-linear lateral dynamics through iterative back-stepping. The proposed controller performance meets the expectation of functionality while driving within the designed system constraints of lateral motion dynamics. This research work deals with the erratic system which remains unstable whenever value of reference signal becomes reasonably high. The adjustable parameters provided in the control input signal of adaptive lateral control aids to control such abrupt changes in motion dynamics specifically in multiple curvature road. The hybrid approach of model reference adaptive lateral control aided with linear heading control is designed in MATLAB and validated in virtual platform of Carmaker. The complex road structure has been modeled in Carmaker to aid in simulation-based testing of lateral control with vehicle model in loop. The performance of model substantiates the efficacy and robustness of proposed control mechanism.