In this paper, an adaptive control scheme based on using neural networks is designed to guarantee the desired behavior of a micro-robot which is equipped with vibrating actuators and follows the principle of slip-stick movement. There are two tiny shaking motors which have been utilized to run the micro-class robotic system. Dynamic modeling equations are expressed by considering the spring coefficient of the bases. After that, the effect of the spring on the foundations was investigated. In addition to designing neural-based controller, an AI-based system identifier has been developed to help the controller update its parameters and achieve its desired targets. Using this method, several specific paths for the movement of this micro robot are simulated. Based on the simulation results, the proposed controlling strategy guarantees acceptable performance for tracking different paths due to plotted near-zero errors and handles the nonlinear behavior of the micro-robot system.
翻译:在本文中,一个基于使用神经网络的适应性控制计划旨在保证微型机器人的预期行为,该机器人配备振动动器,并遵循滑板运动的原则。有两个微小摇晃发动机被用于运行微型类机器人系统。动态模拟方程式通过考虑基底的春季系数来表达。此后,对弹簧对基底的影响进行了调查。除了设计神经控制器外,还开发了一个基于AI的系统标识符,以帮助控制器更新其参数并实现其预期目标。使用这一方法,模拟了该微型机器人移动的若干具体路径。根据模拟结果,拟议的控制战略保证了跟踪因绘制接近零误差而导致的不同路径的可接受性能,并处理了微型机器人系统的非线性行为。