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Book ChapterDOI

Design of PSO-Based PI Controller for Tension Control in Web Transport Systems

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TLDR
Simulation studies indicate that the proposed PI controller tuned using particle swarm optimization (PSO) for WTS exhibits good performance optimization by maintaining constant web tension without violating physical constraints.
Abstract
Web transport systems (WTS) are widely employed in industries to transport materials as a long sheet (web) from one section to another. Maintaining web tension along the transit is imperative as it accounts for material integrity and quality. Hence, an efficient web tension controller is needed to provide performance optimization and reduced production down time. Conventional controllers such as PI controllers have several shortcomings, such as performance distortion in noisy environment, inability to handle interactions among the process variables and lack of optimality. This investigation presents an offline optimization-based PI controller tuned using particle swarm optimization (PSO) for WTS to control the web tension. Simulation studies indicate that the proposed controller strategy exhibits good performance optimization by maintaining constant web tension without violating physical constraints.

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Citations
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Journal ArticleDOI

Improved PI neural network-based tension control for stranded wire helical springs manufacturing

TL;DR: In this article, an improved proportion integral neural network (PINN) with a simplified actuator model was proposed for the winding process of stranded wire helical springs (SWHSs).
Journal ArticleDOI

Lyapunov Based Reference Model of Tension Control in a Continuous Strip Processing Line with Multi-Motor Drive

TL;DR: The article describes design and experimental verification of a new control structure with reference model for a multi-motor drive of a continuous technological line in which the motors are mutually mechanically coupled through processed material to achieve a zero steady-state control deviation of the tension in the strip.
Journal ArticleDOI

Stable and Robust Tension Controller for Middle Section of Continuous Line

TL;DR: In this article, a stable and robust tension controller for the middle sections of continuous lines designed on the basis of the second Lyapunov method was presented, and its application in the middle section of a concrete line with two machines.
References
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Proceedings ArticleDOI

Particle swarm optimization

TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Journal ArticleDOI

Modeling and robust control of winding systems for elastic webs

TL;DR: The objective is to control a web transport system with winder and unwinder for elastic material and an H/sub /spl infin// robust control strategy with varying gains is shown to render the control more robust to the radius variations.
Proceedings ArticleDOI

Active disturbance rejection control for web tension regulation

TL;DR: In this article, a new control method is proposed for tension regulation in a web transport system based on a unique active disturbance rejection control (ADRC) strategy, which actively compensates for dynamic changes in the system and unpredictable external disturbances.
Journal ArticleDOI

Tension control for winding systems with two-degrees-of-freedom H/sub /spl infin// controllers

TL;DR: In this paper, the authors present a robust control with two degrees of freedom (2DOF) and gain scheduling for web transport systems, where the main concern is to control independently speed and tension in spite of perturbations such as radius variations and changes of setting point.
Journal ArticleDOI

A Decentralized Model Reference Adaptive Controller for Large-Scale Systems

TL;DR: In this paper, a decentralized model reference adaptive controller (MRAC) for a class of large-scale systems with unmatched interconnections is developed, where the states of the subsystems can asymptotically track the desired reference trajectories.
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