Optimizing the Series Cascade Control Structure for Non‐minimum Phase System Regulation

Ashish Kumar Singhal, Manish Yadav, Vijay Yadav, Jyoti Deshmukh, Manish Billore, Hirak Mazumdar
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Abstract

This work elucidates the control of integrating a non‐minimum phase system via a series cascade scheme with fractional‐order P.I. (Proportional–Integral) plus D (Derivative) controller. The traditional Internal Model Control (IMC) is adopted for inner loop controller design. The feedback D controller is synthesized with the outer loop process model, showing the proposed work's universality. The outer loop controller is suggested in the IMC framework after the accountability of fractional‐filter and inverse response compensator. This combination is revealed to enhance performance without compromising robustness. The Riemann sheet principle is explored to compute the stability of the suggested controller. The sensitivity analysis has asserted the robustness. More importantly, the optimal value of controller settings is achieved via the Teaching Learning Based Optimization (TLBO) algorithm. This TLBO algorithm uses an objective function that minimizes Integral Square Error (ISE). Two illustrative problems are utilized to examine the recommended control structure's virtue.This article is protected by copyright. All rights reserved.
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优化非最小相位系统调节的串联级联控制结构
本研究阐明了通过分数阶 P.I.(比例-积分)加 D(微分)控制器的串联级联方案对非最小相位系统进行集成控制的问题。内环控制器设计采用了传统的内部模型控制(IMC)。反馈 D 控制器与外环过程模型合成,显示了所提议工作的通用性。在 IMC 框架中,建议采用分式滤波器和反响应补偿器。结果表明,这种组合能在不影响稳健性的情况下提高性能。利用黎曼表原理计算了建议控制器的稳定性。灵敏度分析证明了其稳健性。更重要的是,控制器设置的最佳值是通过基于教学学习的优化(TLBO)算法实现的。该 TLBO 算法使用的目标函数是最小化积分平方误差 (ISE)。本文受版权保护。本文受版权保护,保留所有权利。
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