Abstract
Tensegrity structures are pin-jointed assemblies of struts and cables that are held together in a stable state of stress. Shape control is a combination of control-commands with measurements to achieve a desired form. Applying shape control to a near-full-scale deployable tensegrity structure presents a rare opportunity to analytically and experimentally study and control the effects of large shape changes on a closely coupled multi-element system. Simulated cable-length changes provide an initial activation plan to reach an effective sequence for self-stress. Controlling internal forces is more sensitive than controlling movements through cable-length changes; internal force-control is thus a better objective than movement-control for small adjustments to the structure. The deployment of a tensegrity structure in previous work was carried out using predetermined commands. In this paper, two deployment methods and a method for self-stress are presented. The first method uses feedback cycles to increase speed of deployment compared with implementation of empirically predetermined control-commands. The second method consists of three parts starting with a path-planning algorithm that generates search trees at the initial point and the target point using a greedy algorithm to create a deployment trajectory. Collision and overstress avoidance for the deployment trajectory involve checks of boundaries defined by positions of struts and cables. Even actuator deployment followed by commands obtained from a search algorithm results in the successful connection of the structure at midspan. Once deployment at midspan is achieved by either method, a self-stress algorithm is implemented to correct the position and element forces in the structure to the design configuration prior to in-service loading. Modification of deployment control-commands using the feedback method (with twenty cycles) compared with empirically predetermined control-commands successfully provides a more efficient deployment trajectory prior to midspan connection with up to 50% reduction in deployment time. The path-planning method successfully enables deployment and connection at midspan with a further time reduction of 68% compared with the feedback method (with twenty cycles). The feedback control, the path-planning method and the soft-constraint algorithm successfully lead to efficient deployment and preparation for service loading. Advanced computing algorithms have potential to improve the efficiency of complex deployment.
Highlights
Many deployable structures today, such as retractable roofs (Gantes et al, 1989; Akgün et al, 2011) and spacecraft appendages (Pellegrino, 1995; Liu et al, 2014) deploy along one-degree of freedom
This paper describes a novel methodology for deployment of a near-full-scale pedestrian bridge
The number of control commands is shown on the horizontal axis and the average actuation cumulative cable-length change of continuous cables shown on the vertical axis
Summary
Many deployable structures today, such as retractable roofs (Gantes et al, 1989; Akgün et al, 2011) and spacecraft appendages (Pellegrino, 1995; Liu et al, 2014) deploy along one-degree of freedom. Tensegrity structures are light-weight and deformable structures that are useful in applications such as flat roofs (Csölleová, 2012), floors (Fest et al, 2004; Motro et al, 2006), shells (Skelton et al, 2001), and towers (Schlaich, 2003). These structures are composed of bars in compression surrounded by a network of cables in tension to maintain stability (Pellegrino and Calladine, 1986; Motro, 2011; Snelson, 2012). In order to control the structure, either struts (Averseng and Dubé, 2012; Amendola et al, 2014) or cables (Sultan, 2014) have been actuated for shape control
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