Kharlamenko V. Adaptive control of dynamic load in crimp cage of blooming mill with using the method of fuzzy definition of work rolls' slip

The thesis is devoted to decision of actual scientific task of more efficient control of dynamic load of kinematic lines of the blooming mill by applying adaptive control of speed gradient method and determination of slip on the basis of fuzzy inference. The research of performance of model of kinematic lines of the blooming mill was conducted, improved by taking into account the growing area of non-linear characteristics of the external friction between the work rolls and metal. Improved approach to process control automation compression metal blooming through a combination of adaptive control based on robust speed gradient algorithm and fuzzy inference. Using the proposed approach the algorithms of the system adaptive process control compression of metal, performed their simulation. Implementation results obtained thus reducing the load on the dynamic electromechanical equipment blooming mill compared to existing control systems, implemented on the basis of classic regulators, and increase productivity assembling by reducing cycle time by 0.5 % rolling time and repair downtime. Industry - automation of management processes (technical sciences).