The measurement acceleration of the forcebalance accelerometer (FBA) is calculated by the control force when the feedback control force is balanced with the external inertia force. Thus, the forcebalance control algorithm is the core of a forcebalance sensor. Most of the traditional control algorithms aim at minimizing the offset position of the sensitive elements from the equilibrium, which limits the measurement accuracy and applicable bandwidth of the forcebalance accelerometer. In this paper, taking a MEMS forcebalance sensor as the object, an optimal control algorithm of forcebalance accelerometer is proposed for minimizing the measurement error. By introducing measurement error as a new state variable, the difficult forcebalance control is transformed into an optimal control problem for response minimization, from which the analytical expression of the optimal control force is obtained. Based on the proposed control strategy, the realtime highprecision detection of unknown acceleration signal is realized. Numerical simulations are carried out for three different types of input acceleration signals (step, periodic and random). It is found that the proposed algorithm can accurately detect all kinds of input acceleration signals, and the frequency band of the measured signal reaches up to kHz. At the same time, the vibration response of the sensitive element can be effectively controlled, which guarantees the large dynamic range of a FBA. Our work provides the basis for the research of high performance forcebalance accelerometer with highprecision and wide frequency band.