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CLC number: TU391; TU392.5

On-line Access: 2016-04-05

Received: 2015-05-19

Revision Accepted: 2015-11-30

Crosschecked: 2016-03-08

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Citations:  Bibtex RefMan EndNote GB/T7714


Peng-cheng Yang


Yao-zhi Luo


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Journal of Zhejiang University SCIENCE A 2016 Vol.17 No.4 P.253-272


Active structures integrated with wireless sensor and actuator networks: a bio-inspired control framework

Author(s):  Peng-cheng Yang, Yan-bin Shen, Yao-zhi Luo

Affiliation(s):  Zhejiang Provincial Key Laboratory of Space Structures, Zhejiang University, Hangzhou 310058, China

Corresponding email(s):   luoyz@zju.edu.cn

Key Words:  Active structures (AS), Wireless sensor and actuator networks (WSAN), Shape control, Bio-inspired control

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Peng-cheng Yang, Yan-bin Shen, Yao-zhi Luo. Active structures integrated with wireless sensor and actuator networks: a bio-inspired control framework[J]. Journal of Zhejiang University Science A, 2016, 17(4): 253-272.

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%T Active structures integrated with wireless sensor and actuator networks: a bio-inspired control framework
%A Peng-cheng Yang
%A Yan-bin Shen
%A Yao-zhi Luo
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%DOI 10.1631/jzus.A1500109

T1 - Active structures integrated with wireless sensor and actuator networks: a bio-inspired control framework
A1 - Peng-cheng Yang
A1 - Yan-bin Shen
A1 - Yao-zhi Luo
J0 - Journal of Zhejiang University Science A
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A1500109

One of the main problems in controlling the shape of active structures (AS) is to determine the actuations that drive the structure from the current state to the target state. Model-based methods such as stochastic search require a known type of load and relatively long computational time, which limits the practical use of AS in civil engineering. Moreover, additive errors may be produced because of the discrepancy between analytic models and real structures. To overcome these limitations, this paper presents a compound system called WAS, which combines AS with a wireless sensor and actuator network (WSAN). A bio-inspired control framework imitating the activity of the nervous systems of animals is proposed for WAS. A typical example is tested for verification. In the example, a triangular tensegrity prism that aims to maintain its original height is integrated with a WSAN that consists of a central controller, three actuators, and three sensors. The result demonstrates the feasibility of the proposed concept and control framework in cases of unknown loads that include different types, distributions, magnitudes, and directions. The proposed control framework can also act as a supplementary means to improve the efficiency and accuracy of control frameworks based on a common stochastic search.

This paper presents a compound systems called WAS, which is the AS combined with a wirelesses sensor and actuator network (WSAN).


创新点:1. 提出一类主动结构混合系统--集成无线传感器-执行器网络的主动结构(WAS);2. 通过模仿动物反射活动以及节律运动,提出WAS的两层级仿生控制框架。
方法:1. 将无线传感器-执行器网络引入主动结构,组成混合系统,建立离散的基本模型(图1);2. 结合仿生思想,按照两层级控制框架编制基本控制流程(图3和4);3. 通过仿真模拟,将无线传感器-执行器网络嵌入主动三棱柱张拉整体结构,运用仿生控制框架对张拉整体结构在多种工况下进行形状控制,验证所提概念和方法的可行性与有效性(图7和13)。
结论:1. 与以随机搜索算法为主的基于模型的形状控制方法相比,本文所提出的混合系统及其仿生控制框架,计算量极小,因此可快速应对外部作用的变化;2. 对于未知荷载作用,本文提出的仿生控制框架无需进行荷载识别,因此适应性更强;3. 由于不依赖于有限元模型,该仿生控制框架避免了来自实际结构与数值模型的误差,因此控制精度更高。


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