While cable-driven parallel robots (CDPRs) feature wide workspaces, strong payload capacity, and good scalability, they are hindered by nonlinear dynamics, redundant actuation, and non-negative tension constraints. Traditional control strategies, including PID, adaptive methods, and robust nonlinear approaches, often suffer from chattering, parameter sensitivity, and difficulties in ensuring feasible cable tensions. This paper proposes a hybrid control framework that integrates Sliding Mode Control (SMC) with Particle Swarm Optimization (PSO) to achieve precise trajectory tracking and orientation stability in a four-cable planar CDPR. The SMC ensures robustness against model uncertainties and external disturbances, while PSO optimally tunes the controller gains within bounded ranges to mitigate chattering and enhance stability. A null-space–based positive tension converter is incorporated to enforce non-negative tensions, minimizing deviation from the nominal wrench. Simulation results on circular trajectories demonstrate that the proposed approach maintains tracking accuracy with position errors below 3%, suppresses angular deviations within 0.34°, and ensures feasible tension profiles within 0–60 N. The framework highlights the effectiveness of PSO-optimized SMC in addressing robustness, stability, and physical constraints, offering practical insights for deploying CDPRs in automated and precision tasks.