Abstract— This paper presents a control algorithm for single-input single-output systems with time-varying model parameters based on the integration of sliding mode control (SMC) and recursive least squares (RLS). The proposed algorithm is evaluated through simulations on a virtual direct current motor under abrupt parameter changes at 𝑡=10 seconds and 𝑡=20 seconds. Without RLS, the system output fails to converge to the desired velocity, while the presence of RLS reduces the error but results in slow convergence. Hence, the influence of control parameters, weighting coefficients (𝑐), and forgetting factor (𝜆), along with their interaction, was analyzed. Specifically, reducing 𝜆 to 0.99 and increasing the SMC gain 𝑐 up to 5 improves the convergence speed but introduces significant overshoot (up to 150 rpm). For this reason, a damping function is proposed and incorporated into the control signal. Simulation results show that the proposed controller completely eliminates overshoots at the initial time (𝑡<2 s), reduces settling time to under 2 seconds after each model change, and maintains steady-state errors within ∣𝑒∣<2 rpm despite input disturbance in the range [−0.1,0.1] voltage. The overshoot at 𝑡=10 seconds and 𝑡=20 seconds is reduced to 80 rpm and 114 rpm, respectively, without causing instability. As a result, it confirms the effectiveness of the proposed method in achieving fast, robust, and smooth tracking performance under parameter uncertainties.