Learning, Self-Diagnosis And Multi-Objective Control Of An Active Tensegrity Structure

Adam, Bernard; Smith, Ian F. C.

doi:10.1007/1-4020-4891-2_36

Cited by 6 publications

(6 citation statements)

References 5 publications

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“…Another important concept related to the topic of smart structures is learning control (Adam, Smith [4]). The point of this phenomenon, also known as a case-based reasoning, is that the structure has a base, in which variable possible cases and control commands are stored.…”

Section: Fig 1 Schematic Diagram Showing a Smart Conceptmentioning

confidence: 99%

“…A group of scientists from Ecole Polytechnique Fédérale de Lausanne has conducted different research on smart tensegrity structures (Adam, Smith [4]; Korkmaz et al [5]; Rhode-Barbarigos et al [6]). One of their projects concerned a full-scale model of a smart modular tensegrity structure, equipped with three displacement sensors and ten actuators.…”

Section: Introductionmentioning

confidence: 99%

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Active Control Of Smart Tensegrity Structures

Sabouni-Zawadzka

2014

Archives of Civil Engineering

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The topic of smart structures, their active control and implementation, is relatively new. Therefore, different approaches to the problem can be met. The present paper discusses variable aspects of the active control of structures. It explains the idea of smart systems, introduces different terms used in smart technique and defines the structural smartness. The author indicates differences between actively controlled structures and structural health monitoring systems and shows an example of an actively controlled smart footbridge.The analyses presented in the study concern tensegrity structures, which are prone to the structural control through self-stress state adjustment. The paper introduces examples of structural control performed on tensegrity modules and plates. An influence of several self-stress states on displacements is analyzed and a study concerning damage due to member loss is presented.

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Section: Fig 1 Schematic Diagram Showing a Smart Conceptmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Active Control Of Smart Tensegrity Structures

Sabouni-Zawadzka

2014

Archives of Civil Engineering

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“…Moreover, tensegrities have some unique features that result from the infinitesimal mechanisms, which are stabilized by self-stress forces. It is possible to control their static and dynamic properties by adjusting the pre-stressing forces [15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Inherent Properties of Smart Tensegrity Structures

Sabouni-Zawadzka¹,

Gilewski²

2018

Applied Sciences

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Abstract:The present paper discusses different aspects of the structural control of smart systems with a focus on tensegrity structures. Special attention is paid to unique features of tensegrity systems, referred to by the authors as inherent, which are induced by infinitesimal mechanisms that are balanced with self-stress states. The following inherent properties are defined: self-control, self-diagnosis, self-repair and self-adjustment (active control). All these features are thoroughly described and illustrated on a series of analyses performed on numerical models of various tensegrity systems. The presented examples of the analyses of different tensegrity modules and multi-module structures show that it is possible to control their properties by adjusting the pre-stressing forces. Moreover, it is proven that the adjustment of self-stress forces in a tensegrity system allows one to repair the damaged structure by compensating the damaged member.

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“…Researchers have considered this issue and offered some solutions. For example, calibration of a numerical model with a correction based on measurements (Shea et al, 2002;Fest et al, 2003) or an artificial neural network (ANN) used to modify numerical models (Domer et al, 2003a) may help reduce the discrepancy, locate some simple structural damage (Adam and Smith, 2006), and identify self-stress to some extent (Angellier et al, 2012). Nevertheless, the effect and generality of such measures are limited.…”

Section: Motivation and Difficultymentioning

confidence: 99%

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

Yang

Shen

Luo

2016

J. Zhejiang Univ. Sci. A

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Abstract: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.

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Learning, Self-Diagnosis And Multi-Objective Control Of An Active Tensegrity Structure

Cited by 6 publications

References 5 publications

Active Control Of Smart Tensegrity Structures

Active Control Of Smart Tensegrity Structures

Inherent Properties of Smart Tensegrity Structures

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

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