Topology optimization of structural systems considering both compliance and input observability

Recent advances in flexible and wireless sensors, soft materials, and additive manufacturing, have stimulated demands for developing intelligent systems that can achieve multidisciplinary objectives (e.g., mechanical strength, thermal conductivity, state and input estimation, controllability, and others). Existing studies often decouple these objectives through sub-system level design, e.g., topology and material design for mechanical and thermal properties, and filter and sensor/actuator design for observability and controllability, assuming that the sub-systems have minimal influences to each others. To investigate the validity of this assumption, we take a unique angle at studying how the topology of the system influences both structural performance (e.g., compliance under static loads) and input observability (e.g., the error in estimating the loads). We reveal a tradeoff between these two objectives and derive the Pareto frontier with respect to the topology. This preliminary result suggests the necessity of a multiobjective formulation for designing intelligent structures, when significant tradeoffs among system objectives exist.