Design of an IMCPID Optimized Neural Network for Stepless Flow Control of Reciprocating Mechinery

It is usually difficult to design a controller for nonlinear multiple-input and multiple-output (MIMO) system. The methodological approach taken in this study mixed methodology based on PID-type internal model control (IMC) method neural network (NN) optimization algorithm. NN designed adjusting the sole parameter IMCPID compensating characteristic changes non-linearity stepless flow control. In study, simulation of MIMO system with strong coupling carried out. results indicate that proposed has better performance settle time, overshoot, robustness set-point tracking accuracy compared other considered methods.