In a DC motor's double closed-loop control system with the traditional sliding mode control (SMC) method for the speed loop controller

the sliding mode parameters are often difficult to be tuned

resulting in the poor control of the DC motor. To solve the problem

a method based on the improved genetic algorithm (IGA) is proposed to tune the sliding mode parameters. Firstly

the transfer functions of the speed loop of the DC motor's double closed-loop control system are established

and the optimal values of the sliding mode parameters are tuned with the IGA-combined speed loop MATLAB/Simulink simulation model. Finally

the sliding mode speed controller with the optimal values is simulated and compared with the conventional PID common sliding mode speed controller and the common GA-tuned sliding mode speed controller. The hardware-in-the-loop experimental platform for the DC motor's double closed-loop control is built based on the dSPACE 1202 semi-physical simulation platform for verification. The simulation results show that the IGA-tuned sliding mode speed controller can make the DC motor's double closed-loop control system have the advantages of no overshoot

fast response and strong robustness

proving that the method can effectively solve the parameter tuning problem of the sliding mode speed controller.