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In this paper, an adaptive control scheme based on using neural networks isdesigned to guarantee the desired behavior of a micro-robot which is equippedwith vibrating actuators and follows the principle of slip-stick movement.There are two tiny shaking motors which have been utilized to run themicro-class robotic system. Dynamic modeling equations are expressed byconsidering the spring coefficient of the bases. After that, the effect of thespring on the foundations was investigated. In addition to designingneural-based controller, an AI-based system identifier has been developed tohelp the controller update its parameters and achieve its desired targets.Using this method, several specific paths for the movement of this micro robotare simulated. Based on the simulation results, the proposed controllingstrategy guarantees acceptable performance for tracking different paths due toplotted near-zero errors and handles the nonlinear behavior of the micro-robotsystem.

Designing an AI-Based Adaptive Controller Augmented with a System Identifier for a Micro-Class Robot Equipped with a Vibrating Actuator