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The superheated steam temperature object of thermal power plant has the characteristics of time lag, inertia and time-varying parameters. The control quality of the conventional proportional integral derivate controller with fixed parameters will decrease after the object characteristics change. The generalized predictive control strategy of superheated steam temperature based on neural network local multi-model switching can achieve the goal of designing sub-controllers for fixed models underdoi:10.2298/tsci2104949z fatcat:mwhoqptmlzeszoaoqrczqpihpi