Nonlinear separation control with neural learning for evaporator in energy conversion plant

Nonlinear separation control with neural learning for complex nonlinear system was proposed. This method combined a nonlinear separation method with an artificial neural network. With learning from actual data, it can not only realize nonlinear control of complex nonlinear systems, but also improve the control performance. Based on this method, outlet working fluid heat rate control of an evaporator in a spring thermal energy conversion plant, as a typical application of the proposed method, was realized. The simulation results verified the effectiveness of the proposed method.