Freeway work zone with lane closure has a direct negative impact on travel time, safety, and environmental sustainability. The capacity drop at the onset of the congestion can also further reduce the discharging rate at the work zone area and worsen traffic conditions. Existing studies have developed various variable speed limit (VSL) control methods to mitigate the congestion; however, a simple yet robust VSL control strategy that considers the nonlinearity induced by the capacity drop is still lacking. To address the above-mentioned issue, this study proposes a VSL strategy using a nonlinear traffic flow model and a discrete-time sliding mode control for freeway work zone. The developed traffic flow model incorporates the nonlinearity caused by the capacity drop at the work zone using the cell transmission model. The sliding mode controller is designed to drive the traffic state, which is acquired from the built traffic flow model, to the desired equilibrium state with different convergence rates. Under speed limit constraints, the VSL scheme is generated to regulate the traffic and mitigate the congestion. The proposed system is implemented and evaluated using the traffic microscopic simulator SUMO. The results indicate that the proposed VSL control can consistently improve the traffic mobility, safety, and environmental sustainability under the noisy traffic demand and different control scenarios. Compared with the uncontrolled scenario, the developed system shows improvement by approximately reducing 17% of the average travel time, 90% of the safety risk, and 6% of NOx, CO2 emissions, and fuel consumption.