This paper presents a reduced‐order observer for state‐dependent coefficient factorized nonlinear systems. By considering that a partial knowledge of the state vector is available from measurements, estimating the full state vector may be unnecessary, which consequently reduces the order of the observer and thus avoids unnecessary implementation issues. In this manuscript, the asymptotic convergence of the proposed reduced‐order observer is established when an adequate state‐dependent factorization for the nonlinear system is obtained. This paper demonstrates the ease of synthesizing reduced‐order observers for state‐dependent coefficient factorized nonlinear systems. The effectiveness of the proposed observer is illustrated in real‐time for the optimal tracking control of a linear induction motor.