This article discusses quantum algorithms as effective tools for solving problems related to dynamic control. Compared to traditional methods, quantum computing can significantly accelerate the process of finding optimal solutions. The focus is on the Variational Quantum Eigensolver, which is used to mini-mize the energy function of a time-varying system. The article examines various stages of solving a dynamic control problem, starting from defining the system and the objective function, and concluding with the implementation of quantum computations and analysis of the results. It is crucial to select the appropriate algorithm and optimize parameters to effectively manage complex systems. The research findings indicate that quantum algorithms can greatly enhance the speed and efficiency of solving dynamic control problems. This suggests that they can be applied in new areas such as robotics, financial optimization, and energy system management. To fully leverage the potential of quantum computing, the article emphasizes the need for further research in this field.