Parameter Identification of Integrated Model of Hydraulic Turbine Regulating System With Uncertainties Using Three Different Approaches

In this paper, three novel parameter identification methods are developed and used to solve the unknown parameters problem of integrated model of hydraulic turbine regulating system with uncertainties. The first and second methods are designed based on different parameter observers using dynamic system stability theorem, which are referred to as unknown parameter observer and synchronization-based parameter observer, respectively, while the third method is designed based on an ant lion optimizer (ALO) algorithm, which is referred to as the ALO-based estimator. Performance of the three methods are compared in various aspects, including the orders, the structure, and the independence of the identification system. Results show that the unknown parameter observer has the lowest identification system orders, while the synchronization-based parameter observer has the simplest system structure, and the ALO-based estimator owns the best system independence.