The Application Of An Adaptive PID Controller In Pinch Roll Of Bilateral Shear

Wuyang Iron and Steel Company shear plate rolling mill in the 1990s, domestically produced equipment. Electrical control systems were the original simulation system and it has incomplete drawings of aging equipment. The original simulation system's operation and maintenance is very difficult. As the electrical parameters are not equal, resulting in eight motor's speed range and the output torque of the motor is not the same. The nether roller shaft of Pinch roller forms even mechanical axis through the synchronous axis. Because of the output torque is not equal; the torque is produced at the synchronous axis. Synchronous axis is damaged. On the pressure the above Roller and plates Synchronous through friction. If the output torque of the rollers is not equal, the level of torque will be produced in plate, which make deviate plate and produce defective scrap.When the old system operates, phenomena of electrical damage and plate deviation have occurred from time to time, which affect the quality and productivity of product. To solve the problem of deviation, although series resistance is used in the motor's armature and loop of excitation, fine-tune the torque and speed of motor. In a certain extent this method eased the deviation, not only fine-tuning is very difficult and consumption of energy is huge, but also the actual controlling effect is not good. Deviation was often happened, that not only resulting in producing scrapped plate, but also giving birth to a waste of resources and seriously affects quality and quantity.The effective combination of the plant, we put forward the digital transformation of electrical control system to pinch roll. We decided to adopt the single neuron model that relates to adaptive PID control system, so as to transform the old system. Model relates to Adaptive PID control single neuron that is the simple structure of conventional PID control, which has robustness and high reliability. The PID is also adaptive automatic identification, which has self-tuning and self-learning ability. After transformation to the digital system, this is a typical double-loop control of speed and current combining single neuron's adaptive control system. The system is applied to shear. The system has become control mode of "1:3" and "dragged seven".