Developing intelligent tensegrity structures with stochastic search

Shea, Kristina; Fest, Etienne; Smith, Ian F. C.

doi:10.1016/s1474-0346(02)00003-4

Cited by 65 publications

(38 citation statements)

References 21 publications

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“…It is sometimes difficult to implement realtime control. Without case-base or any learning methods, it takes a relatively long time to give an effective solution in response to a new loading event (Shea et al, 2002;Smith, 2003;Fest et al, 2004). It is long even for quasi-static control, not to mention for real-time control.…”

Section: Motivation and Difficultymentioning

confidence: 99%

“…Adaptability to loads can sometimes be limited. In those model-based stochastic search procedures for the numerical FEM calculation, the load conditions have to be known or prescribed to the computer or the human controllers (the users) (Shea et al, 2002;Fest et al, 2003;, or at least the load has to be partially defined so that the load identification work can be done first (Adam and Smith, 2007a;. In situations where the only piece of information is the structural deformation (from totally unknown loads), the control task will be difficult.…”

Section: Motivation and Difficultymentioning

confidence: 99%

“…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%

“…To satisfy the serviceability objective, the actuations (length changes of the active members) have to be determined in shape control of AS, so that the structure can be driven to the target configuration. Approaches based mainly on stochastic search methods have been proposed to find feasible actuations (Shea et al, 2002;Domer et al, 2003b;Domer and Smith, 2005;Xu and Luo, 2008;2009). Fest et al (2003; designed AS prototypes with telescopic struts and proposed control strategies based on stochastic search to maintain a top-surface slope.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Motivation and Difficultymentioning

confidence: 99%

Section: Motivation and Difficultymentioning

confidence: 99%

Section: Motivation and Difficultymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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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“…The first method simulates traditional design through parametric analyses, while the second uses a direct stochastic search called PGSL (Probabilistic Global Search Lausanne). PGSL is a stochastic sampling method for global optimization that has been shown to give better performance than other stochastic optimization methods for engineering tasks such as configuration, diagnosis and control [16,[18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Design of tensegrity structures using parametric analysis and stochastic search

Rhode-Barbarigos

Jain

Kripakaran

et al. 2009

Engineering with Computers

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Tensegrity structures are lightweight structures composed of cables in tension and struts in compression. Since tensegrity systems exhibit geometrically nonlinear behavior, finding optimal structural designs is difficult. This paper focuses on the use of stochastic search for the design of tensegrity systems. A pedestrian bridge made of square hollow-rope tensegrity ring modules is studied. Two design methods are compared in this paper. Both methods aim to find the minimal cost solution. The first method approximates current practice in design offices. More specifically, parametric analysis that is similar to a gradient-based optimization is used to identify good designs. Parametric studies are executed for each system parameter in order to identify its influence on response. The second method uses a stochastic search strategy called Probabilistic Global Search Lausanne (PGSL). Both methods provide feasible configurations that meet civil engineering criteria of safety and serviceability. Parametric studies also help in defining search parameters such as appropriate penalty costs to enforce constraints while optimizing using stochastic search. Traditional design methods are useful to gain an understanding of structural behavior. However, due to the many local minima in the solution space, stochastic search strategies find better solutions than parametric studies.

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