Adaptive Dynamic State Prediction Control Algorithms for Quantitative Weighing System

In the most industrial processes, weighing machines are designed to automatically fill one or more types of the containers with a predetermined weight of particulates raw material using a controller. The performance of the machine is closely related to the accuracy of measurement and speed of dynamic response, which are contradictory. For a gravimetric filling machine, a novel adaptive dynamic state prediction control (ADSPC) algorithm running in the controller is proposed in this paper to regulate conflicts. This algorithm will consider the weighing process as a finite state. State migration is depended on the resulting weight and current state. The resulting weight is determined by the weight of measurement and current state. Compared with normal algorithm and simple prediction algorithm separately under the same condition, the result indicated that the algorithm is effective and feasible.