Wheeled robot data-driven iterative learning control method under DOS attack

Abstract

The invention discloses a wheeled robot data-driven iterative learning control method under DOS attacks. The wheeled robot data-driven iterative learning control method comprises three steps of constructing a bottom layer data model, designing a kinematics controller and setting an event triggering mechanism. On the premise of ensuring the expected stability performance, the updating times of the controller are reduced, and bandwidth resources are saved; meanwhile, the controller is designed only by using I / O measurement data generated by the dynamical model without depending on specific parameters of the dynamical model, so that the difficulty in the aspect of model decoupling is reduced, and the method is suitable for WMR systems with different types of mechanical structures and is more beneficial to practical engineering popularization; in addition, the method can introduce an iteration domain to get rid of the constraint of an early convergence process under the condition of considering network malicious DOS attacks and introducing an event triggering mechanism, and achieves complete trajectory tracking of the wheeled mobile robot in the whole time domain, thereby greatly improving the stability and reliability of the operation of the wheeled robot.

Description

technical field [0001] The invention belongs to a robot control method and technology, in particular to a data-driven iterative learning control method for a wheeled robot under DOS attack. Background technique [0002] With the rapid development of science and technology in recent years, mobile robots have been widely used in engineering applications such as industrial logistics, military reconnaissance, agricultural irrigation and space exploration. Trajectory tracking control is a basic problem that robots need to solve in practical applications. Trajectory tracking can usually be divided into two forms, one is path tracking, which only requires the robot to run according to the desired path, and does not need to consider the speed issue; the other is real-time trajectory tracking, which requires WMR to simultaneously monitor the position and speed of the desired trajectory For tracking, the goal is to reach a specific location at a specific speed. Since the first type ...

AI Technical Summary

Problems solved by technology

However, the above works are all based on the kinematics model to design the controller, without considering the influence of the changes in the mechanical characteristics of the dynamic model such as WMR mass, moment of inertia and control torque in practical applications on the trajectory tracking performance

Moreover, the above controllers all assume that WMR can immediately catch up with the desired speed at the initial moment, and the problem of speed jump in WMR trajectory tracking is not discussed. This kind of sudden trajectory tracking is difficult to apply in engineering

In particular, the above control strategies are all gradual and stable control along the time domain. Although WMR can achieve stable trajectory tracking, it takes a certain amount of time to converge in the initial stage of trajectory tracking, and it cannot guarantee that the robot can be achieved in the entire time domain. full trajectory tracking

Images