Accurate Parameter Estimation of a Hydro-Turbine Regulation System Using Adaptive Fuzzy Particle Swarm Optimization

摘要: Parameter estimation is an important part in the modeling of a hydro-turbine regulation system (HTRS), and results determine final accuracy model. A normally non-minimum phase with strong nonlinearity time-varying parameters. For parameter such nonlinear system, heuristic algorithms are more advantageous than traditional mathematical methods. However, most heuristics based their improved versions not adaptive, which means that appropriate parameters algorithm need to be manually found keep performing optimally solving similar problems. To solve this problem, adaptive fuzzy particle swarm optimization (AFPSO) dynamically tunes according model error proposed applied HTRS. The simulation studies show AFPSO contributes lower higher identification compared some algorithms. Importantly, it avoids possible deterioration performance caused by inappropriate selection.