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 ...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.展开更多
The grillage adaptive beam string structure(GABSS)is a new type of smart structure that can self-adjust its deformation and internal forces through a group of active struts(actuators)in response to changes in environm...The grillage adaptive beam string structure(GABSS)is a new type of smart structure that can self-adjust its deformation and internal forces through a group of active struts(actuators)in response to changes in environmental conditions.In this paper,an internal force control method based on a gradient–genetic algorithm(GGA)is proposed for the static control of a tensioned structure(especially the GABSS).Specifically,an optimization model of the GABSS is established in which the adjustment values of the actuators are set as the control variables,and the internal force of the beam is set as the objective function.The improved algorithm has the advantage of the global optimization ability of the genetic algorithm and the local search ability of the gradient algorithm.Two examples are provided to illustrate the application of the GGA method.The results show that the proposed method is practical for solving the internal force control problem of the GABSS.展开更多
基金financially supported by the National Natural Science Foundation of China(21625304)the Natural Science Foundation of Fujian Province(2019J06018)the Natural Science Foundation of Xiamen,China(3502Z20206008)。
基金Project supported by the National Key Technology R&D Program of China(No.2012BAJ07B03)the National Natural Science Foundation of China(Nos.51178415 and 51578491)
文摘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.
基金supported by the National Key R&D Program of China(No.2017YFC0806100)the National Natural Science Foundation of China(No.51578491)。
文摘The grillage adaptive beam string structure(GABSS)is a new type of smart structure that can self-adjust its deformation and internal forces through a group of active struts(actuators)in response to changes in environmental conditions.In this paper,an internal force control method based on a gradient–genetic algorithm(GGA)is proposed for the static control of a tensioned structure(especially the GABSS).Specifically,an optimization model of the GABSS is established in which the adjustment values of the actuators are set as the control variables,and the internal force of the beam is set as the objective function.The improved algorithm has the advantage of the global optimization ability of the genetic algorithm and the local search ability of the gradient algorithm.Two examples are provided to illustrate the application of the GGA method.The results show that the proposed method is practical for solving the internal force control problem of the GABSS.
