Backstepping Control for Multi-Machine Web Winding System

Abstract

-This work treat the modeling and simulation of non-linear dynamic behavior of a web winding process during traction. We designate by a winding process any system applying the cycles of unwinding, transport, treatment, and winding to various flat products. This system knows several constraints, such as the thermal effects caused by the frictions, and the mechanical effects provoked by metal elongation, that generates dysfunctions due to the influence of the process conditions. Several controllers are considered, including Proportional-integral (PI) and Backstepping control. This paper presents the study of Backstepping controls strategy of the winding system. Our winding system is simulated in MATLAB SIMULINK environment, the results obtained illustrate the efficiency of the proposed control with no overshoot, and the rising time is improved with good disturbances rejections comparing with the classical control law.

A study of sensorless vector control of IM using neural network luenberger observer

“…The objective is to make the similar thing with the asynchronous motor. This is exactly the of the vector control [11].…”

Imperfect Roll Arrangement Compensation Control based on Neural Network for Web Handling Systems

“…Sliding Mode Control (SMC) [6] is employed in [7], in which tension observers are introduced to eliminate the requirement of loadcells. Backstepping control is applied in [8][9][10][11] to counter the nonlinearity effects in R2R systems. An indirect tension control is proposed in [12], where the web tension is manipulated indirectly via distance information between two consecutive rolls.…”

On finite-time output feedback sliding mode control of an elastic multi-motor system

“…Multi-motor drive systems have been employed in systems moving paper, metal, material being quite popular in manufacturing systems and researched by many authors in the recent times. The control method utilized artificial neural network (ANN) technique has been presented by Bouchiba et al, [1]. However, the disadvantage is to investigate the appropriate networks with associated learning rules in control design.…”

“…However, the difficulties of the control design lie in the fact that measurement of this belt tension by using sensors. The sliding mode control (SMC) technique based state feedback control enables to eliminate influence of disturbances and unknown parameters was proposed in [1], [4]. In [4], the sliding mode controller was combined with disturbance observer as well as iterative learning control (ILC), feedforward controller.…”

“…Unlike the description was established in[1]-[4], this work considers multi-motor systems in presence of nonlinear property, backlash, friction, elastic phenomenon. Therefore, the transfer-function based approach in[1]-[4] has not been mentioned in this paper due to these challenges. The main control objective to find the velocities12 , rr  obtaining the tracking of state variables vector = [∆ 1 , ∆ 2 , 1 , 2 , 21 , 12…”