Experience mapping based predictive controller (EMPC) is a recently developed controller based on the concepts of Human Motor Control. It has been demonstrated to out-perform other classical controllers like proportional-derivative (PD), model reference based adaptive controller (MRAC), linear quadratic regulator (LQR) and the linear quadratic Gaussian (LQG) for both Type-1 and Type-0 systems. This paper analyses the stability and efficiency of EMPC for Type 1 systems. EMPC uses rectangular pulse input as control action for well-damped Type 1 systems and a first order decay input for under-damped Type 1 systems. The simulation results of EMPC for position control of a DC motor with a load coupled through a flexible shaft are presented as a case study to derive and prove the stability criterion. The efficiency of EMPC on a practical system is analysed in terms of energy dissipated in the armature resistance of the motor and the same is compared with PD, MRAC, LQR, LQG controller. Further, the computational cost of EMPC is discussed and compared with traditional controllers from the point of view of implementation.