<p>This paper presents optimized nonlinear control strategies to improve Crazyflie Quadrotor Unmanned Aerial Vehicle (CF-QUAV) trajectory tracking. Using Newton–Euler laws, we formulate the dynamics of Crazyflie (CF) and introduce four nonlinear controllers: Sliding Mode Control (SMC), Proportional–Integration–Derivative SMC (PID-SMC), Backstepping (BS), and Integral-Backstepping (IBS). With tuned gains based on the Genetic Algorithm (GA), these controllers address limitations when using cascaded-PID controllers, especially in high-speed maneuvering. Simulation-based experiments evaluate the efficiency and stability of each controller’s trajectory tracking at different speeds. The results show that the PID-SMC and IBS controllers maintain stability up to <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\({1.2\ m/s}\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>1.2</mn> <mspace width="4pt" /> <mi>m</mi> <mo stretchy="false">/</mo> <mi>s</mi> </mrow> </math></EquationSource> </InlineEquation>, with IBS demonstrating superior performance up to <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\({1.5\ m/s}\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>1.5</mn> <mspace width="4pt" /> <mi>m</mi> <mo stretchy="false">/</mo> <mi>s</mi> </mrow> </math></EquationSource> </InlineEquation>. Statistical metrics, root mean square error (RMSE), <i>R</i>-squared (<InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(R^2\)</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mi>R</mi> <mn>2</mn> </msup> </math></EquationSource> </InlineEquation>), and regression coefficient (<i>r</i>) are used to evaluate the performance of each proposed controller, highlighting their effectiveness in trajectory tracking.</p>