In nuclear reactors,the conventional PI controller parameter tuning method is cumbersome and complex,with strong dependence on human experience,which makes it difficult to achieve the simultaneous co-optimization of multiple PI controller parameters in the reactor.To study this problem,a small pressurised water reactor nuclear steam supply control system is established with the reactor coolant average temperature and steam pressure controller parameters as the optimization objectives,and a Non Dominated Sorting Genetic Algorithm-II(NSGA-II)is used to achieve the parameter optimization of the nuclear steam supply control system.The results show that the optimized control system effectively reduces the overshoot and response time of the controlled objects,improves the control performance of the control system,and at the same time lessens the dependence on human experience and achieves the intelligence of the parameter tuning process.
Small pressurized water reactor nuclear steam supply systemPI controller parameterMulti-objective co-optimizationNSGA-II
维普
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