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Immunity-Based Optimal Estimation Approach for a New Real Time Group Elevator Dynamic Control Application for Energy and Time Saving

机译:新型实时群电梯动态控制节能与基于免疫的最优估计方法

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摘要

Nowadays, the increasing use of group elevator control systems owing to increasing building heights makes the development of high-performance algorithms necessary in terms of time and energy saving. Although there are many studies in the literature about this topic, they are still not effective enough because they are not able to evaluate all features of system. In this paper, a new approach of immune system-based optimal estimate is studied for dynamic control of group elevator systems. The method is mainly based on estimation of optimal way by optimizing all calls with genetic, immune system and DNA computing algorithms, and it is evaluated with a fuzzy system. The system has a dynamic feature in terms of the situation of calls and the option of the most appropriate algorithm, and it also adaptively works in terms of parameters such as the number of floors and cabins. This new approach which provides both time and energy saving was carried out in real time. The experimental results comparatively demonstrate the effects of method. With dynamic and adaptive control approach in this study carried out, a significant progress on group elevator control systems has been achieved in terms of time and energy efficiency according to traditional methods.
机译:如今,由于建筑物高度的增加,越来越多地使用群组电梯控制系统,这使得在时间和节能方面需要开发高性能算法。尽管文献中对此主题进行了许多研究,但由于它们无法评估系统的所有功能,因此仍然不够有效。本文研究了一种基于免疫系统最优估计的新方法,用于群体电梯系统的动态控制。该方法主要基于通过遗传,免疫系统和DNA计算算法优化所有调用的最佳方式的估计,并使用模糊系统对其进行评估。该系统在呼叫情况和最合适的算法选项方面具有动态功能,并且还可以根据楼层和机舱数量等参数自适应地工作。这种既节省时间又节省能源的新方法是实时进行的。实验结果比较证明了该方法的有效性。通过这项研究中的动态和自适应控制方法,按照传统方法,在时间和能源效率方面,群电梯控制系统已经取得了重大进展。

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