<p>Delta robots offer high performance and flexibility due to their rigid parallel structure. However, the inherent nonlinearities in their dynamics present a significant challenge for precise trajectory tracking. This paper proposes a hybrid dynamic surface control with sliding mode control (DSC-SMC) strategy to enhance the accuracy and stability of trajectory tracking for 3-DOF delta robots. The proposed DSC-SMC method introduces a recursive control design that systematically constructs both the feedback control law and Lyapunov function, incorporating a low-pass filter to avoid repeated differentiations as required in traditional backstepping, thereby reducing computational complexity and improving real-time implementation. Furthermore, the robustness of sliding mode control is preserved while significantly mitigating chattering effects through the use of a first-order low-pass filter, which replaces abrupt switching with a smooth continuous approximation. This smooth control signal enhances system durability and extends the operational lifespan. The closed-loop stability of the system is rigorously guaranteed via Lyapunov-based analysis, ensuring input-to-state stability (ISS), while the use of the low-pass filter also helps eliminate the explosion of complexity, resulting in a simpler control structure. Simulation results in MATLAB/Simulink, conducted with a circular trajectory under unknown external disturbances demonstrate that DSC-SMC outperforms dynamic surface control (DSC), dynamic surface control with neural networks (DSC-NN), and backstepping sliding mode control (BSP-SMC). Specifically, DSC-SMC reduces the tracking error of the three joint angles to asymptotically zero values, achieves convergence times of 0.1 seconds for joint 1 and 0.2 seconds for joints 2 and 3, and maintains a stable torque of ±6 Nm. These results confirm the superiority and practical applicability of DSC-SMC for high-precision tasks such as high-speed pick-and-place operations and 3D printing.</p>