In this paper, an improved particle swarm optimization (IPSO) algorithm is proposed. Besides the individual best position and the global best position, a nominal average position of the swarm is introduced in IPSO. The performance of IPSO is compared to different PSO variants with five well-known benchmark functions. The experimental results show that the proposed IPSO algorithm improves the searching performance on the benchmark functions. And then, IPSO, as well as other PSO variants, is applied to optimal tuning of Proportional-Integral-Derivative (PID) gains for a typical PID control system of water turbine governor. The computer simulation results of an actual hydro power plant in China show that IPSO algorithm has stable convergence characteristic and good computational ability, and it is an effective and easily implemented method for optimal tuning of PID gains of water turbine governor. (C) 2010 Elsevier Ltd. All rights reserved.