Currently, the main focus in the automation of technological processes is on developing control systems that enhance the quality of the control process. Because the systems being controlled are often complex, multidimensional, and nonlinear, quantum computing algorithms offer an effective solution. Although there are several intelligent control methods available to improve the quality of technological processes, each has certain drawbacks. Quantum algorithms, which rely on the principles of quantum correlation and superposition, are designed to optimize control while minimizing energy and resource consumption. This article discusses the diesel fuel hydrotreating process, a critical step in oil refining. The primary goal of hydrotreating is to enhance fuel quality by removing sulfur, nitrogen, and oxygen compounds. To accurately model this process, it is essential to consider not only the external factors affecting it but also its physical characteristics. By doing so, the mathematical model becomes more precise. Based on this approach, a quantum fuzzy control system for the diesel fuel hydrotreating process was developed using quantum algorithms. These algorithms can rapidly analyze large amounts of data and make decisions. At the same time, a computer model of a fuzzy quantum control system for the process of hydrotreating diesel fuel was constructed, and a number of computational experiments were carried out. As a result, a 1.8% reduction in energy costs for the diesel fuel hydrotreating process was achieved.