The objective of this paper was to investigate the possibility of using neuro-fuzzy algorithms in the real-time follower control system of a wheeled mobile robot in the presence of variable basic conditions of work and their assessment of the quality of control. For this purpose the intelligent servo motion controller was developed based on neural networks and fuzzy logic systems whose the task is to compensate the non-linearity and uncertain modeling of the mobile robot's traffic. This system has been designed in such a way as to allow for modification of its properties at any moment due to the changing working conditions of the mobile robot. The object of control is a two-wheeled mobile robot.
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