Adaptive Inventory Control Based on Fuzzy Neural Network under Uncertain Environment

• Published in: Complexity (New York, N.Y.) Vol. 2020; no. 2020; pp. 1 - 10
• Main Authors: Ge, Jianqiao, Zhang, Songtao
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 29.07.2020; Hindawi; John Wiley & Sons, Inc; Wiley
• Subjects: Accuracy; Adaptive control; Analysis; Artificial neural networks; Computer simulation; Control algorithms; Control theory; Controllers; Fuzzy control; Fuzzy logic; Fuzzy sets; Inventory; Inventory control; Inventory management; Laplace transforms; Laws, regulations and rules; Mathematical models; Methods; Neural networks; Supply chains; Tracking
• ISSN: 1076-2787; 1099-0526
• DOI: 10.1155/2020/6190936

In order to achieve the actual inventory effectively tracking the target inventory under uncertain environment, this paper investigates an adaptive inventory controller for the production-inventory system. First, an uncertain production-inventory model is constructed, and then, the uncertainty of the production-inventory model is approximated by a fuzzy neural network. Secondly, in terms of the design of adaptive control law, the adaptive inventory controller is developed. Under the adaptive inventory controller, the actual inventory can track the target inventory in real time and the production-inventory system can be robustly stable in uncertain environment. Finally, the results of three simulation experiments show that the proposed adaptive inventory controller can realize both the fast tracking speed and the high tracking accuracy.