# THE SYNTHESIS OF STEERING RULES FOR STABILIZING ROAD TRAIN REVERSE MOTION TO SOLVE THE TASK OF REACHING A SET GOAL

• Dmitry Tatievskyi Zaporizhzhya State Engineering Academy
Keywords: road train, vehicle-trailer system, alpha-stabilization, fuzzy logics, SDRE, kinematic model, steering law, APIOpenMaple, wheel base, folding angle, orientation angles, path, Lyapunov’s direct method

### Abstract

Mathematical models of a road train are developed to study both its direct and reverse motion. The laws for the automatic steering system turning vehicle steering wheels to achieve the required trailer direction when moving reverse are synthesized. A road train with a hitching unit on the tractor truck rear axle directly schematic constructions (an “on-axle hitching” model) are used. The kind of kinematic mathematic model for describing a road train moving reverse at low speeds without wheels side slipping is satisfactory. In this condition its motion is defined by geometry only independent from masses, momentums and friction forces.

The steering laws are synthesized with the help of alpha-stabilizing approach, according to Lyapunov’s direct method using fuzzy logics mathematical tool and a solution method depending on the Riccati equation state (SDRE).

The task of reaching a set goal has been solved by calculating the folding angle when the target belongs to the calculated path for the case of curvilinear motion and via calculating the matching tractor truck and trailer orientation angles for direct motion.

The received results have been rendered as phase portraits in the Maple environment and meshes in Meshlab, simulated in Unity 3D and with a robotic installation getting control information generated automatically

### Author Biography

Dmitry Tatievskyi, Zaporizhzhya State Engineering Academy

Division of Software Engineering

### References

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Published
2017-11-28
How to Cite
Tatievskyi, D. (2017). THE SYNTHESIS OF STEERING RULES FOR STABILIZING ROAD TRAIN REVERSE MOTION TO SOLVE THE TASK OF REACHING A SET GOAL. Technology Transfer: Fundamental Principles and Innovative Technical Solutions, 37-39. https://doi.org/10.21303/2585-6847.2017.00482
Section
Computer Sciences