Abstract

Well-designed adaptive structures are able to meet typical strength and deflection requirements using significantly less material and energy resources compared with passive structures. Structural adaptation through sensing and actuation is employed to counteract the effects of loading through control of the internal load-path and the structure shape (external geometry). The design criterion is minimization of the structure whole-life energy comprising an embodied part in the material and an operational part for adaptation to loading. Recent work has investigated the efficacy of structural adaptation through large shape reconfigurations that involve geometrically non-linear effects. A new design strategy that includes a combination of geometry and actuator placement optimization with non-linear shape control has been formulated, whereby the structure is designed to ‘morph’ into optimal shapes as the load changes. Structures produced by this strategy can meet must stricter deflection limits with respect to passive solutions, which enables new design such as super slender high-rise buildings, bridges and self-supporting roof systems. A near-full scale prototype has been successfully tested validating key assumptions and numerical predictions. A new mechanics-based control algorithm has been developed based on a linear-sequential formulation which combines shape optimization and non-linear force method. This formulation enables accurate shape control using minimum computational cost, which makes it suitable for real-time applications. Classification based on supervised learning has been employed to infer position and magnitude of the applied load as well as to improve control accuracy. Experimental results are in good accordance with numerical predictions showing that effective stress homogenization can be achieved through controlled large shape changes, which results in 39% embodied energy savings with respect to an equivalent weight-optimized passive structure.