<p>Nowadays, it is important to efficiently use energy resources in <br /> production systems, optimize production processes, and ensure system flexibility <br /> in the face of uncertainty and variability. Production lines and technical systems <br /> are often subject to random influences that can reduce their efficiency and product <br /> quality. It is also necessary for the system to be able to make fast and effective <br /> decisions, optimize resources, and adapt to changes that occur from time to time. <br /> We propose an adaptive control model based on technical cognitive systems, <br /> which utilizes quantum genetic algorithms to address these issues. With the help <br /> of quantum computing and genetic algorithms, systems are optimized, which <br /> increases the efficiency of production processes. The model helps save energy <br /> resources and accelerate the decision-making process in multidimensional systems. <br /> As a result, production systems become more efficient and flexible, which improves <br /> product quality and maximizes resource use.</p>