At present, the scarcity of fresh water is one of the biggest global problems. One of the solutions to the shortage of fresh water is the treatment of salt water and the recycling of used water. Although there are several advanced water treatment methods available, there are still certain deficiencies. The primary objective of effluent remediation on a global scale is to decrease energy consumption and resource depletion. Improving wastewater treatment technologies, reducing energy consumption, and increasing water purity also depend on the proper control of the process. One of the urgent issues is the creation of effective models of the synthesis of the control system, taking into account the complexity of the technological process and the non-linearity and uncertainty of data. This article discusses a control system referred to for developing intelligent control systems via quantum nondeterministic inference. This design strategy allows for the handling of unexpected situations when information about the structure of the object is incomplete. A new method has been created to use quantum algorithms to solve optimization and combinatorial logic problems (hybrid and parallel) in artificial intelligence. This method shows how well and efficiently the control process is working. A quantum system has been designed to regulate the wastewater treatment process under unknown external effects by utilizing quantum algorithms that can analyse vast amounts of data quickly and make rapid judgements. The implementation of this system made it possible to reduce the energy consumption of wastewater treatment by 1.5%.