Han Yaozhen

Load Reduction Pitch Control for Large Scale Wind Turbines based on Sliding Mode

With the wind turbines being produced toward to large scale and light weight, the flexibility of blade, drive mechanism and tower increase apparently. Loads suffered by wind turbines during operation become increasingly intricate. Some control approaches could be used to cut down these loads in orde to expand life cycle of generating sets. Aiming at the full load operation zone above rated wind speed, conventional control target is only considering rotating speed of wind turbine and without considering the loads, such that these loads could not be restrained effectively. This paper proposes a multi-objective sliding mode pitch control approach based on a new double-power reaching law. It can control rotating speed of wind turbine and decrease balanced loads of tower, blade and drive mechanism. Simulation is implemented under Matlab/Simulink and the results verified effectiveness of the designed control scheme.

A Back Propagation Neural Network Sliding Mode Controller for Ship Course Nonlinear System

A back propagation network sliding mode variable structure control method is proposed for ship course nonlinear control. Neural network is used to simulate the functional relation between state hyperplane of the system and the exponential reaching law. A hyperbolic tangent function is applied to replace the saturation function to realize the boundary method of sliding mode control. Chattering is greatly reduced and simulation results demonstrate the presented control method has good adaptability and high robustness.