Study of workshop network stability based on pinning control in disturbance environment

Abstract

In the production process, the manufacturing behavior and all the essential factors are affected by several disturbance factors, showing a complex dynamic fluctuation law. It makes the stability control process a difficult problem in environmental constraints. In this paper, the workshop production process is considered, and an improved coupled map lattice workshop production network state model is proposed. On this basis, the controller with the function of resource load protection is designed, and the network state model of the workshop based on the pinning control is developed. Three kinds of stability control strategies, SAC (Self-adaption Control) , SC (Self-acting Control) and PC (Pinning Control) , are designed based on disturbance triggering behavior and node state transition rules. In addition, two control effect evaluation indexes, RTS (Recovery Time Steps) and NFT (Node Failure Times) are designed. Considering the actual production data of diesel fuel injection system parts production workshop as example, the model is simulated and verified. The results show that under different disturbance intensities, compared with the SAC strategy, the RTS-Average value of the PC strategy is reduced by 29.83% on average, and the NFT-Average values are reduced by 46.9% on average. This proves that the pinning control strategy has certain advantages in controlling time length and propagation scale of disturbance propagation.