Inertial stabilized platform (ISP) is a vital component in modern tracking system which can segregate unsettling influence, keep altitude reference and rapidly realize identification and tracking of the target. For accurate tracking, the platform should be able to continuously point towards the target in presence of disturbances as well as parametric uncertainties associated with system modelling which normally degrade system performance. To tackle these challenges, different kinds of control strategies have been reported to achieve desired performance. However, there is an inevitable design trade-off between tracking and disturbance rejection capability as control performance decreases with the increase in system robustness. To alleviate this problem, the present work proposes a robust two-loop cascade control strategy where genetic algorithm (GA) optimized proportional–integral–derivative (PID) in the outer-loop facilitates precision tracking of the target. In the inner loop, lower-order robust controller designed by approximate generalized time moment (AGTM)/approximate generalized Markov parameter (AGMP) model matching approach is used to retain the robustness characteristics of [Formula: see text] controller to mitigate disturbances and model parametric uncertainties. System performance is verified through simulation as well as hardware implementation on a laboratory-fabricated three-axis gimbal platform prototype. The results show 48% improvement in tracking performance and 39.69% improvement in the rejection time of step disturbance in comparison with conventional PID control strategy.