To enhance the precision of quadrotor landings on a fixed platform, the integration of control algorithms alongside the navigation system is essential. This paper presents the design of an optimal controller aimed at improving quadrotor performance during soft landings. A primary focus of the study is to minimize the energy consumption of the quadrotor's drive motors. Lower energy demands enable the use of smaller batteries, resulting in a lighter and more efficient aerial vehicle. To achieve this optimization, we employ a meta-heuristic algorithm known as the Gray Wolf Optimizer (GWO), which fine-tunes control coefficients to accelerate system response and reduce power usage. This research introduces a novel hybrid control approach—the Gray Wolf Sliding Mode Control (GWOSMC) algorithm. The key contribution of this paper lies in the strategic implementation of GWOSMC, which demonstrates approximately a 22-fold improvement in energy reduction compared to conventional Sliding Mode Control (SMC). To assess the effectiveness of these control schemes, we conduct simulations using MATLAB. The results clearly show that GWOSMC significantly outperforms traditional SMC methods in terms of energy efficiency.