Optimized Load Frequency Controller Performances With a Reduced Number of Decision Variables: A Gravitational Search Algorithm-Based Method

IF 1.9 Q3 COMPUTER SCIENCE, CYBERNETICS IEEE Systems Man and Cybernetics Magazine Pub Date : 2023-01-01 DOI:10.1109/MSMC.2022.3208393
Arabinda Ghosh, A. Ray, Omkar Singh, M. Jamshidi
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Abstract

Ensuring stability and maintaining performances of the load frequency controller (LFC) are stimulating tasks. A state feedback controller (SFC) with a generalized range of operation satisfying the necessary and sufficient conditions for system stability along with optimized performances through the gravitational search algorithm (GSA) are proposed. The proposed range is dependent on the system parameters. The agent-based systems in the literature consider the dimension of an agent as per the number of decision variables of the problem. The proposed method reduces the number of decision variables to obtain the controller gains and to use in the optimization process. The proposed method is validated through extensive results for different objective functions, contemplating both the steady state and the transient requirements as well as a consideration of different perturbed system parameters and variations in the input disturbances. Results and comparative studies with popular control techniques and optimization algorithms testify that the proposed method maintains system stability and improves the system performances while considering different system parameters, parametric uncertainties, and variations in input disturbances.
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基于引力搜索算法的决策变量数量减少的负载频率控制器性能优化方法
确保负载频率控制器(LFC)的稳定性和维护性能是一项激励任务。提出了一种广义的状态反馈控制器(SFC),其工作范围满足系统稳定的充分必要条件,并通过引力搜索算法(GSA)优化了系统的性能。建议的范围取决于系统参数。文献中基于智能体的系统根据问题的决策变量的数量来考虑智能体的维度。该方法通过减少决策变量的数量来获得控制器增益并用于优化过程。通过对不同目标函数的广泛结果验证了所提出的方法,考虑了稳态和暂态要求,并考虑了不同的扰动系统参数和输入扰动的变化。结果表明,该方法在考虑不同系统参数、参数不确定性和输入扰动变化的情况下,保持了系统的稳定性,提高了系统性能。
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来源期刊
IEEE Systems Man and Cybernetics Magazine
IEEE Systems Man and Cybernetics Magazine COMPUTER SCIENCE, CYBERNETICS-
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6.20%
发文量
60
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