Gas Turbine Aerodynamics Improvement Via a Design of Intelligent Fractional Control

Debbah Abdesselam, Kherfane Hamid, Kelaiaia Ridha
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引用次数: 3

Abstract

Abstract Gas turbines are complex processes characterized by the instability and uncertainty of various sources. The range of useful operating in an axial compressor which is part of a turbine gas is limited by aerodynamic instabilities that are surge and rotating stall. This paper presents two intelligent fractional order sliding mode controllers. At first, a robust sliding fractional surface form is proposed to deal with hazardous phenomena which limit compression systems performance, and speed transitions, which can lead to temporary stall development, pressure drop at the output, degrade the effective operation of compressors and consequently gas turbines. Second, to reduce the chattering/fluctuation in control, a fuzzy logic and finite time criterion are used as switching control at the reaching phase in the sliding mode control. Additionally, the controller gains are obtained by offline multi-objective Particle swarm optimization (MOPSO) search. Finally, the surge and rotating stall of a Variable Speed Axial Compressor (VSAC) in a gas turbine are investigated under the system nonlinearities and also in presence of an external disturbance and perturbations. The simulation results signify the performance of the two MOPSO-based fractional sliding mode controllers.
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基于智能分式控制设计的燃气轮机空气动力学改进
燃气轮机是一个复杂的过程,其特点是各种来源的不稳定性和不确定性。作为涡轮气体的一部分,轴向压气机的有效运行范围受到喘振和旋转失速等空气动力学不稳定性的限制。本文提出了两种智能分数阶滑模控制器。首先,提出了一种鲁棒滑动分数曲面形式来处理限制压缩系统性能和速度变化的危险现象,这些危险现象可能导致暂时失速发展,输出压力下降,降低压缩机和燃气轮机的有效运行。其次,为了减少控制中的抖振/波动,在滑模控制中采用模糊逻辑和有限时间准则作为到达相位的切换控制。此外,通过离线多目标粒子群优化(MOPSO)算法获得控制器增益。最后,研究了燃气轮机变频轴流压气机在系统非线性和外部扰动作用下的喘振和转失速问题。仿真结果验证了两种基于mopso的分数阶滑模控制器的性能。
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