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The control of water pump water supply is an important part of the intelligent irrigation control system. The water supply in the water supply process is beneficial to the development of crop roots and the absorption of minerals in the soil within the optimal control range. In the intelligent irrigation control, due to the nonlinear, timevarying and hysteresis problems of the pump control, the traditional proportion integration differentiation (PID) control is difficult to achieve good control effects. In order to solve the instability problem of pump control in intelligent irrigation system, based on the traditional PID control algorithm, the seeker optimization algorithm (SOA) was used to optimize PID control. The results showed that the optimal control algorithm can effectively solve the problems of nonlinearity, timevarying and hysteresis in the control of intelligent irrigation pumps. In order to verify the actual effect of SOA optimization PID control, it was compared with particle swarm optimization (PSO) optimized PID control and genetic algorithms (GA) optimized PID control. The experimental simulation results showed that the PID control based on SOA optimization had the shortest response time, smallest overshoot, and no oscillation in the steady state process. Therefore, it was suitable for pump control in intelligent irrigation systems.