<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In gas turbine process, the axial compressor is subjected to aerodynamic instabilities because of rotating stall and surge associated with bifurcation nonlinear behaviour. This paper presents a Genetic Algorithm and Particle Swarm Optimization (GA/PSO) of robust sliding mode controller in order to deal with this transaction between compressor characteristics, uncertainties and bifurcation behaviour. Firstly, robust theory based equivalent sliding mode control is developed via linear matrix inequality approach to achieve a robust sliding surface, then the GA/PSO optimization is introduced to find the optimal switching controller parameters with the aim of driving the variable speed axial compressor (VSAC) to the optimal operating point with minimum control effort. Since the impossibility of finding the model uncertainties and system characteristics, the adaptive design widely considered to be the most used strategy to deal with these problems. Simulation tests were conducted to confirm the effectiveness of the proposed controllers.</p></abstract>

In gas turbine process, the axial compressor is subjected to aerodynamic instabilities because of rotating stall and surge associated with bifurcation nonlinear behaviour. This paper presents a Genetic Algorithm and Particle Swarm Optimization (GA/PSO) of robust sliding mode controller in order to deal with this transaction between compressor characteristics, uncertainties and bifurcation behaviour. Firstly, robust theory based equivalent sliding mode control is developed via linear matrix inequality approach to achieve a robust sliding surface, then the GA/PSO optimization is introduced to find the optimal switching controller parameters with the aim of driving the variable speed axial compressor (VSAC) to the optimal operating point with minimum control effort. Since the impossibility of finding the model uncertainties and system characteristics, the adaptive design widely considered to be the most used strategy to deal with these problems. Simulation tests were conducted to confirm the effectiveness of the proposed controllers.

GA/PSO Robust Sliding Mode Control of Aerodynamics in Gas Turbine

Department of Petro-chemical and Process Engineering

Acta Universitatis Sapientiae, Electrical and Mechanical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"GA/PSO Robust Sliding Mode Control of Aerodynamics in Gas Turbine"}

In gas turbine process, the axial compressor is subjected to aerodynamic instabilities because of rotating stall and surge associated with bifurcation...

GA/PSO Robust Sliding Mode Control of Aerodynamics in Gas Turbine

Online veröffentlicht: 01. Feb. 2019

Seitenbereich: 42 - 66

Eingereicht: 15. Sept. 2018

Akzeptiert: 15. Dez. 2018

DOI: https://doi.org/10.2478/auseme-2018-0003

Schlüsselwörter
aerodynamic instabilities, variable speed axial compressor (VSAC), sliding mode control (SMC), adaptive robust control, genetic algorithm (GA), particle swarm optimization (PSO)

© 2018 Abdesselam Debbah et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

GA/PSO Robust Sliding Mode Control of Aerodynamics in Gas Turbine

Online veröffentlicht: 01. Feb. 2019

Seitenbereich: 42 - 66

Eingereicht: 15. Sept. 2018

Akzeptiert: 15. Dez. 2018

DOI: https://doi.org/10.2478/auseme-2018-0003

Schlüsselwörteraerodynamic instabilities, variable speed axial compressor (VSAC), sliding mode control (SMC), adaptive robust control, genetic algorithm (GA), particle swarm optimization (PSO)

© 2018 Abdesselam Debbah et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
aerodynamic instabilities, variable speed axial compressor (VSAC), sliding mode control (SMC), adaptive robust control, genetic algorithm (GA), particle swarm optimization (PSO)