Computer simulation of nuclear reactor control by means of heuristic learning controller

A trial of application of two techniques of Artificial Intelligence: heuristic Programming and Learning Machines Theory for nuclear reactor control is presented. Considering complexity of the mathematical models describing satisfactorily the nuclear reactors, value changes of these models parameters in course of operation, knowledge of some parameters value with too small exactness, there appear diffucluties in the classical approach application for these objects control systems design. The classical approach consists in definition of the permissible control actions set on the base of the set performance index and the object mathematical model. The Artificial Intelligence methods enable construction of the control system, which gets during work an information being a priori inaccessible and uses it for its action change for the control to be the optimum one. Applying these methods we have elaborated the reactor power control system. As the performance index there has been taken the integral of the error square. For the control system there are only accessible: the set power trajectory, the reactor power and the control rod position. The set power trajectory has been divided into time intervals called heuristic intervals. At the beginning of every heuristic interval, on the base of the obtained experience, the control system chooses from the control (heuristic) set the optimum control. The heuristic set it is the set of relations between the control rod rate and the state variables, the set and the obtained power, similar to simplifications applied by nuclear reactors operators. The results obtained for the different control rod rates and different reactor (simulated on the digital computer) show the proper work of the system. (author)