Sliding mode controller with improved AGA for supercharged boiler drum water level control

Objectives It is difficult to control the drum water level of a supercharged boiler due to the strong load disturbance in the sailing process. In order to ensure the stability of the drum water level, it is necessary to study drum water level control methods under strong load disturbance. To this end, this paper proposes a sliding mode controller with an improved adaptive genetic algorithm (AGA).

Methods The velocity and accelerated speed of the drum water level error is combined with an S-function to design a sliding mode controller. Its stability is then proven using the Lyapunov stability theorem. On this basis, the sliding mode controller parameters are optimized with the improved AGA.

Results The control performance of the sliding mode controller with improved AGA is compared with that of a PID controller. In response to ramp disturbance signals and step disturbance signals, the sliding mode controller with improved AGA can track the input signal without error. Its stability time is 5 s shorter than that of the PID and its overshoot is lower than that of the PID.

Conclusions The simulation results show that the sliding mode controller with improved AGA is superior to the PID controller.