Controlling complex real-world systems which involve hard deadlines using Artificial Intelligence (AI) techniques attracts the interest of several researchers. The difficulty using AI techniques stems from their unpredictable aspect. Most research on "real-time AI" focuses either on restricted AI techniques that have predictable performance characteristics, or on reactive systems where the power of traditional AI is limited. In this paper, we present an intelligent control strategy based on a progressive scheduling algorithm where the duration of tasks is uncertain. This control strategy can meet deadlines while still using unpredictable AI techniques. This control strategy is based on flexible scheduling algorithm to guarantee or trade-off timeliness and the quality of the solution. The performance of this algorithm is compared to another progressive scheduling approach where the uncertainty of duration is ignored.