Neural Network Control for Rolling Mills
نویسندگان
چکیده
Worldwide, steel and aluminum production and manufacturing is still one of the major basic industries with a huge amount of material and energy consumption. Hence, optimization of the various process control schemes which are involved can lead to signiicant savings. Artiicial Neural Networks are a new information processing technique which provides a novel approach to process control problems and promises major improvements. Therefore, Siemens together with FORWISS has been studying and developing neural control schemes for a number of diierent process control problems which occur at hot line rolling mills (Lindhoo et al., 1994). In this paper we give a brief survey of the diierent control aspects which were tackled with this new approach and comment on their current status.
منابع مشابه
A Neural-net Based Self-tuning Fuzzy Looper Control for Rolling Mills
Looper control is one of the challenging problems in rolling mills. The purpose of the paper is to propose an intelligent control method using fuzzy logic and neural network for improved performance of looper control over conventional loop control methods. The focus of the paper will be on the rule-tuning aspect of the proposed fuzzy looper control. Simulation reults will also be presented to v...
متن کاملA Model-based Predictive Control Scheme for Steal Rolling Mills Using Neural Networks
A capital issue in roll-gap control for rolling mill plants is the difficulty to measure the output thickness without including time delays in the control loop. Time delays are a consequence of the possible locations for the output thickness sensor which is usually located some distance away from the roll gap. In this work, a new model-based predictive control law is proposed. The new scheme is...
متن کاملNeuro-Fuzzy Tension Controller for Tandem Rolling
A fuzzy logic controller (FLC) is designed to maintain constant tension for tandem rolling mills. Envisioning fuzzy inference system as neural network and introducing tutor, backward propagation algorithm is used as self-organization technique for FLC to approach the best parameters under supervision. Simulation results exhibit the generalization and adaptivity of neuro-fuzzy controller in offl...
متن کاملA neural network approach to the control of the plate width in hot plate mills
Deviation of a slab width from the desired value in hot plate mills has caused signijicant yield loss by trimming and demanded tighter width tolerances of rolled plates. This necessitates vertical rolling with considerable width accuracy. In this papec a slab width control system is proposed in order to meet the stringent requirement on the plate dimensional tolerance. The control system adopts...
متن کاملPrediction and optimization of load and torque in ring rolling process through development of artificial neural network and evolutionary algorithms
Developing artificial neural network (ANN), a model to make a correct prediction of required force and torque in ring rolling process is developed for the first time. Moreover, an optimal state of process for specific range of input parameters is obtained using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. Radii of main roll and mandrel, rotational speed of main roll, pr...
متن کامل