Abstract: Aiming at the problems existing in the PID parameter tuning of the traditional hydro-turbine governing system, an optimization strategy based on the improved sparrow search algorithm (ISSA) is proposed. Firstly, the initial distribution of the sparrow population is improved by means of the Tent chaotic map. Secondly, the Lévy flight strategy is adopted in the position update of followers. Meanwhile, four benchmark functions are used to test the algorithm. Finally, the improved algorithm is simulated and verified on the MATLAB platform, and its optimization results are compared with those of the particle swarm optimization (PSO) algorithm and the traditional sparrow search algorithm (SSA) under two working conditions: no-load frequency disturbance and load disturbance. The experimental results show that the improved sparrow search algorithm can effectively improve the control performance.