目的:主动结构的几何形状控制一直是结构控制领域的研究前沿。为满足形状控制目标,一个主要问题就是如何求解主动构件的执行量。以随机搜索算法为核心的基于模型的控制方法逐渐成为主流,但仍存在若干需改善之处,如计算量大、实时性差、不能很好应对未知荷载作用以及实际结构与数值模型间存在差异等。本研究旨在寻求一种控制框架,使其能够在某些场合下具备更好的控制性能。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。 Purpose: The geometric control of active structures has always been the forefront of research in the field of structural control. In order to meet the goal of shape control, a major problem is how to solve the execution volume of active components. The model-based control method with random search algorithm as the core has gradually become the mainstream, but there are still some improvements needed, such as large amount of calculation, poor real-time performance, poor response to unknown loads and differences between the actual structure and the numerical model . This research seeks to find a control framework that will allow better control performance in some situations. Innovative points: 1. Proposed a kind of active structure hybrid system - integrated wireless sensor - actuator network active structure (WAS); 2. By imitating the animal reflex activity and rhythm movement, proposed WAS two-level bionic control framework. Methods: 1.Wireless sensor-actuator networks are introduced into the active structure to form a hybrid system, and a discrete basic model is established (Figure 1); 2.According to the bionic idea, the basic control flow is compiled according to the two-level control framework (Figures 3 and 4) ; 3. Through the simulation, the wireless sensor-actuator network is embedded into the active triangular prism to pull the overall structure, and the bionic control frame is used to shape control the tensioned overall structure under various operating conditions. The feasibility and feasibility of the proposed concepts and methods are verified Sexual and Validity (Figures 7 and 13). Compared with the model-based shape control based on stochastic search algorithm, the proposed hybrid system and its bionic control framework have very little computational complexity and can respond rapidly to the changes of external effects.2. The unknown bifurcation effect, the proposed bionic control framework does not need to carry out load identification, so the adaptability is stronger.3.Because of not relying on the finite element model, the bionic control framework avoids the error from the actual structure and the numerical model, so the control accuracy is more high.