Fixed-Time Coverage Control of Mobile Robot Networks Considering the Time Cost Metric

Abstract

In this work, we studied the area coverage control problem (ACCP) based on the time cost metric of a robot network with an input disturbance in a dynamic environment, which was modeled by a time-varying risk density function. A coverage control method based on the time cost metric was proposed. The area coverage task that considers the time cost consists of two phases: the robot network is driven to cover the task area with a time-optimal effect in the first phase; the second phase is when the accident occurs and the robot is driven to the accident site at maximum speed. Considering that there were movable objects in the task area, a time-varying risk density function was used to describe the risk degree at different locations in the task area. In the presence of the input disturbance, a robust controller was designed to drive each robot, with different maximum control input values, to the position that locally minimized the time cost metric function in a fixed time, and the conditions for maximum control input were obtained. Finally, simulation results and comparison result are presented in this paper.

Adaptive Control Design for Euler–Lagrange Systems Using Fixed-Time Fractional Integral Sliding Mode Scheme

“…Setting up a nonlinear system with appropriate initial conditions has a substantial influence on how long it takes to converge in finite time, and this time changes as the nonlinear system's initial conditions change. A fixed-time control scheme is consequently a substitute that is applied to exactly calculate the convergence time and does not rely on the initial values [29][30][31]. Various fractional-order TSMC (FoSMC) schemes have been designed and applied to several Euler-Lagrange systems.…”