PFTL 101AE-2.0kN 3BSE004213R1 | ABB | Data accuracy convergence module

Description

PFTL 101AE-2.0kN 3BSE004213R1 | ABB | Data accuracy convergence module

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The PFTL 101AE-2.0kN used implementation method is the lookup table method, which is relatively simple but requires a lot of resources. When the network size to be implemented is large and the accuracy requirement is high, there are significant obstacles to the implementation of the lookup table method; Other implementation methods that can be considered are to use polynomials to approximate this nonlinear function in hardware implementation. PFTL 101AE-2.0kN the characteristic of the Sigmoid function entering the saturation zone when the input value is greater than a certain value, only storing the function value near the origin can save a lot of resources and simplify the problem. Its working effect is similar to that of simulation software implemented through non lookup methods. The advantage of neural network hardware implementation is mainly its fast speed, especially when the computational load is large. In real-time control, especially in high-speed rolling processes, the fast operation of advanced control algorithms is particularly important, which is a prerequisite for application in industrial control. The hardware implementation of learning algorithms faces two challenges. One is data. The complexity of flow control lies in the impact of data accuracy on convergence. For simplicity, the PFTL 101AE-2.0kN function is chosen as the sum of squared errors

Discretize equation (17), the actual length of the loop arm is 796mm, and the corresponding loop height at the linear working point is 285mm. Add about 15% to the loop height, which is a step PFTL 101AE-2.0kN signal with an amplitude of 40mm. The structure of the neural network is 4-6. The initial value of the weighting coefficient is taken as a random number in the interval [-0.5, 0.5], and the input mode is selected as r (k), y (k), e (k). 1. Learning rate η= 0.34, inertia coefficient α＝ 0.06. The tension change curve of the decoupled strip steel is shown in Figure 3

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