Nugroho, S.Taha, A. F.Summers, Tyler H.Gatsis, N.2019-09-272019-09-272018-06-279781538654286https://hdl.handle.net/10735.1/6914In most dynamic networks, it is impractical to measure all of the system states; instead, only a subset of the states are measured through sensors. Consequently, and unlike full state feedback controllers, output feedback control utilizes only the measured states to obtain a stable closed-loop performance. This paper explores the interplay between the selection of minimal number of sensors and actuators (SaA) that yield a stable closed-loop system performance. Through the formulation of the static output feedback control problem, we show that the simultaneous selection of minimal set of SaA is a combinatorial optimization problem with mixed-integer nonlinear matrix inequality constraints. To address the computational complexity, we develop two approaches: The first approach relies on integer/disjunctive programming principles, while the second approach is a simple algorithm that is akin to binary search routines. The optimality of the two approaches is also discussed. Numerical experiments are included showing the performance of the developed approaches. © 2018 AACC.en©2018 AACCActuatorsComputational complexityInteger programmingLinear programmingNonlinear programmingarticleNugroho, S., A. F. Taha, T. Summers, and N. Gatsis. 2018. "Simultaneous sensor and actuator selection/Placement through output feedback control." 2018 Annual American Control Conference: 4159-4164, doi: 10.23919/ACC.2018.8431548