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A multi-time-delay compensation controller using a Takagi - Sugeno fuzzy neural network method for high-rise buildings with an active mass damper/driver system

机译:使用Takagi-Sugeno模糊神经网络方法的高层主动阻尼器/驱动器系统的多时滞补偿控制器

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摘要

An active mass damper/driver (AMD) control system with a single mass has such problems as the excessive weight of the auxiliary mass and the insufficient capacity of its driving equipment. It is necessary to work through multiple subsystems to achieve effective control of high-rise buildings. However, the time-delay effect in each subsystem impedes its application in engineering practices. In the paper, an augmented system based on a zero-order hold is proposed for discrete-time systems with multiple time delays, and then the system is designed according to the compensation strategy using a classical linear quadratic regulator algorithm. After that, the sample data obtained from the zero-order hold compensation controller is trained through a Takagi-Sugeno fuzzy neural network method. Finally, a new simplified compensation controller is designed to further shorten the time consuming calculation on the premise of guaranteeing its control effects and parameters. To verify its effectiveness, an AMD system in a high-rise building is regarded as an example, and the proposed methodology is also applied to an experiment of a four-story frame. Both results demonstrate that the method can enhance the performance of an AMD system with multiple time delays.
机译:具有单个质量的主动质量阻尼器/驾驶员(AMD)控制系统具有诸如辅助质量的重量过大和其驱动设备的容量不足之类的问题。必须通过多个子系统来实现对高层建筑的有效控制。但是,每个子系统中的时间延迟效应阻碍了其在工程实践中的应用。本文针对具有多个时滞的离散时间系统,提出了一种基于零阶保持的增强系统,然后采用经典的线性二次调节器算法,根据补偿策略设计了系统。之后,通过Takagi-Sugeno模糊神经网络方法训练从零阶保持补偿控制器获得的样本数据。最后,设计了一种新的简化补偿控制器,在保证控制效果和参数前提下,进一步缩短了计算时间。为了验证其有效性,以某高层建筑中的AMD系统为例,并将所提出的方法也应用于四层框架的实验中。两项结果均表明,该方法可以在多个时间延迟下增强AMD系统的性能。

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