System identification in vibrating structures is useful for structural health monitoring. Onsite structural system identification must be achieved with low energy consumption. Accordingly, semi-active inputs should be considered to apply onsite system identification because they can be generated with low energy consumption. However, conventional identifications that use semi-active inputs could not continuously generate inputs suitable for system identification because of switching failure. Switching failure is caused by the mechanism of the semi-active input generation circuit. Due to switching failure, properties of semi-active inputs deviate from the property suitable for identification. Their results deviate from the results obtained using suitable inputs. Moreover, semi-active identification could not be used for structural health monitoring because they cannot determine the cause of significant variations in the identification results (either because of system identification faults from switching failure or because of structural damage). To solve these drawbacks of semi-active identification, we propose a new strategy to generate semi-active inputs that can realize ideal identification. The proposed strategy has two novelties compared to conventional semi-active identification methods: (1) The strategy prevents switching failures and continuously provides semi-active inputs suitable for identification. (2) The strategy is modeled as an optimization problem and provides appropriate circuit control to generate semi-active inputs suitable for identification by solving binary search. Numerical simulations and experiments confirm that the proposed strategy exhibits better identification performance than the conventional strategies. In addition, small variances are observed in the identification results in all time domains. The semi-active inputs generated by the proposed strategy can contribute to precise structural health monitoring using onsite structural identification because it provides accurate identification results with less variation and energy consumption.