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Genetic-Algorithm-Based Performance Optimization for Non-Linear MIMO System

Genetic-Algorithm-Based Performance Optimization for Non-Linear MIMO System
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Author(s): Anitha Mary Xavier (Karunya University, India)
Copyright: 2018
Pages: 35
Source title: Applied Computational Intelligence and Soft Computing in Engineering
Source Author(s)/Editor(s): Saifullah Khalid (CCSI Airport, India)
DOI: 10.4018/978-1-5225-3129-6.ch003

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Abstract

Environmental regulations demand efficient and eco-friendly ways of power generation. Coal continues to play a vital role in power generation because of its availability in abundance. Power generation using coal leads to local pollution problems. Hence this conflicting situation demands a new technology - Integrated Gasification Combined Cycle (IGCC). Gasifier is one of the subsystems in IGCC. It is a multivariable system with four inputs and four outputs with higher degree of cross coupling between the input and output variables. ALSTOM – a multinational and Original Equipment Manufacturer (OEM) - developed a detailed nonlinear mathematical model, validated made this model available to the academic community and demanded different control strategies which will satisfy certain stringent performance criteria during specified disturbances. These demands of ALSTOM are well known as “ALSTOM Benchmark Challenges”. The chapter is addressed to solve Alstom Benchmark Challenges using Proportional-Integral-Derivative-Filter (PIDF) controllers optimised by Genetic Algorithm.

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