This paper focusses on the study of vibration attenuations for suspended handle models that are generated from power tools using an intelligent active force control (AFC) tuning strategy. Four types of control schemes are comparatively evaluated in suppressing the vibration of the handle, such as proportional-integral-derivative (PID), PID-AFC-crude approximation (AFCCA), PID-AFC-fuzzy logic (AFCFL) and PID-AFC-iterative learning method (AFCILM) control schemes. In all control schemes, the estimated counter force is generated from the actuating force and appropriate estimated mass M* that has been intelligently tuned to counter the system disturbances. The disturbances are modelled based on the power tools vibration (i.e., internal disturbance) and uncertainties during the operation (i.e., external disturbances). The study shows that the AFCCA scheme demonstrates the best performance when the M(CL) is tuned at 0.04 kg. For the AFCFL control scheme, the best response is obtained for the membership function of trapezoidal shape with M(FL) of 0.0403 kg, while for AFCILM control scheme, the best response is achieved when M(ILM) is tuned to 0.04 kg, with both parameters (A and B) set at 0.6. Overall, PID-AFCCA scheme shows the best performances for all of the case studies, followed by PID-AFCFL and PID-AFCILM. The findings of this study can benefit the power tool manufacturers and provide the basis of effectively intelligent controller design for the power tools application.