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The use of feedback control techniques has been gainingimportance in the context of scheduling in real-time systemsas a means to provide predictable performance in the faceof uncertain workload. In this paper, we propose a novelfeedback-based scheduling approach for task scheduling inreal-time systems. We focus on a system with a mobile node,where the mobility characteristics affect task parameters.The objective is to achieve low miss ratio and high CPUutilization. This objective is achieved by feeding back systemperformances and adapting the node' mobility parameters.We study the new approach in a selective herbicidespraying problem in the agricultural production wherein thespeed of an autonomous vehicle (and hence task parameters)is adapted based on weed distribution in the given farmfield. Simulations and analysis show that our approach canachieve low miss ratio and high CPU utilization.