Soft Computing Based Optimum Parameter Design of PID Controller in Rotor Speed Control of Wind Turbines
Sensitivity and robustness is the primary issue while designing the controller for large non-linear systems such as offshore wind turbines. The main goal of this study is a novel soft computing based approach in controlling the rotor speed of wind turbine. The performance objectives for controller design is to keep the error between the controlled output (speed of rotor) and the target rotor speed, as small as possible. The wind turbine involves controlling both the aerodynamics and hydrodynamics response together, therefore in this paper an attempt is being made using soft computing approach. The commonly used proportional – integral – derivative controller (PID controller) for wind turbines employs Ziegler and Nichols (ZN) approach which leads to excessive amplitude in some situations. In this work, the parameters of PID controller are obtained using the conventional method that is ZN along with the artificial intelligence (AI) technique. Two types of AI (i) bacteria foraging optimization algorithm (BFOA) and (ii) particle swarm optimization (PSO) coupled with ZN controller are studied. The controller performance indices are taken as integral square error, steady state error, controller gain, maximum overshoot and settling time. In this work, the idea of model generation and optimization is explored for PID controller. The planned controller strategy would be able to carry out high quality performance which reveal that the proposed controller system can significantly reduce the errors and settling time.
KeywordsWind turbines optimization proportional–integral–derivative controller bacteria foraging optimization algorithm particle swarm optimization
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