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Upgraded Whale Optimization Algorithm for fuzzy logic based vibration control of nonlinear steel structure

机译:基于模糊逻辑的非线性钢结构振动控制的鲸鱼优化升级算法

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In the case of controlling the seismic vibration of a structure, reliance on human knowledge and expert in the formulation of a fuzzy logic controller leads to non-optimal solutions, which makes the use of control devices and algorithm unreasonable. In most cases, the calculated control force for high-rise buildings is very large and the controlled response of the structure is not significantly decreased. To overcome these drawbacks, the parameter tuning of fuzzy systems with optimization algorithms are necessary. This paper focuses on the optimization of a fuzzy controller applied to a seismically excited nonlinear steel building. In the majority of cases, this problem is formulated based on the structural responses in linear range, however in this paper, objective functions and the performance criteria are considered with respect to the nonlinear responses of the structure. An Upgraded Whale Optimization Algorithm is proposed and utilized as the optimization technique for parameter tuning of the fuzzy controller. The performance of the presented upgraded algorithm is compared with the standard Whale Optimization Algorithm and eight different metaheuristic algorithms. The obtained results prove that the upgraded method is capable of providing competitive results.
机译:在控制结构的地震振动的情况下,依赖于人类知识和模糊逻辑控制器的制定专家会导致非最优解,这使得控制设备和算法的使用不合理。在大多数情况下,计算出的高层建筑控制力非常大,并且结构的控制响应不会显着降低。为了克服这些缺点,必须使用优化算法对模糊系统进行参数调整。本文重点研究了应用于地震激励非线性钢结构建筑的模糊控制器的优化。在大多数情况下,此问题是基于线性范围内的结构响应来表述的,但是在本文中,针对结构的非线性响应考虑了目标函数和性能标准。提出了一种改进的鲸鱼优化算法,并将其作为模糊控制器参数整定的优化技术。将提出的升级算法的性能与标准鲸鱼优化算法和八种不同的元启发式算法进行了比较。所得结果证明,改进后的方法能够提供有竞争力的结果。

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