Wind energy converting system sliding mode control method and device based on T-S fuzzy model

Abstract

The invention provides a wind energy converting system sliding mode control method and device based on a T-S fuzzy model. To solve the problem of the fault of an actuator in a wind energy converting system, the T-S fuzzy model is utilized for describing a nonlinear wind energy converting system with uncertain actuator fault information, the approximation accuracy of a controlled object is improved, and a good model foundation is established for sliding mode control. Meanwhile, by means of a sliding mode controller designed based on the linear matrix inequality technology, the stability of the wind energy converting system is guaranteed, and the robustness and fault tolerance of the wind energy converting system are improved. The precise tracking of the rotating speed of a power generator and the electromagnetic torque can be achieved when the uncertain actuator fault exists in the wind energy converting system, and the maximum wind energy capturing of the wind speed below the rated value is achieved, and a valuable reference scheme is provided for efficient and stable running of the wind converting system.

Description

technical field [0001] The invention relates to the technical field of wind energy conversion system control, in particular to a sliding mode control method and device for a wind energy conversion system based on a T-S fuzzy model. Background technique [0002] As one of the most important new energy sources at present, wind energy has been widely used in irrigation, urban power supply and many other fields due to its renewable and environment-friendly characteristics. Wind energy conversion system is one of the most common and effective ways to convert wind energy into electrical energy. However, there are still some important problems in wind power conversion technology, such as: how to achieve the maximum power output of wind turbines. At present, the most commonly used is the MPPT maximum power point tracking control strategy, that is, the maximum wind energy capture is realized through generator torque control, such as CN102477943A. For generator torque control, method...

AI Technical Summary

Problems solved by technology

For generator torque control, methods such as PI control and LPV gain scheduling control are often used. However, the current wind energy conversion system equipment is usually built in remote places, and there are often faults in sensors and actuators, as well as system uncertainties and external disturbances. PI The adaptive ability of the control to the system uncertainty is poor, and it is difficult to control in real time in the wind power system with strong nonlinear multi-parameter changes; LPV control can ensure the stability of the system, but it ignores the external influence of the wind power system during operation The influence of disturbance parameters leads to unsatisfactory maximum wind energy capture effect under its control

[0003] The T-S fuzzy model has been extensively studied because of its simple implementation and strong nonlinear approximation ability, for example, the paper "T-S Fuzzy Modeling and Control Based on Wind Energy Conversion System" (Micro Electric, Issue 10, 2011, Meng Tao, etc.) Firstly, the nonlinear model of the wind energy conversion system is given, and then based on the local linear characteristics of the T-S fuzzy model, the nonlinear model is transformed into multiple linear local models, and then a linear controller is designed for each linear local model, and using the degree function to obtain the global model controller of the wind energy conversion system, and its fuzzy rule is The triangular function is selected as the membership function. Although the selection of appropriate fuzzy rules and fuzzy basis functions can better describe the dynamic characteristics of nonlinear systems, for complex systems such as wind energy conversion systems with uncertain parameters and external disturbances, even with The superior T-S fuzzy modeling method cannot completely eliminate model errors, and advanced robust control technology is still needed to compensate the influence of uncertain factors on the system

The paper "T-S Fuzzy Robust Fault-Tolerant Control of Wind Energy Conversion System" (Information and Control, Vol. 42, No. 6, December 2013, Shen Yanxia, ​​etc.) designed the wind energy conversion system by establishing the T-S fuzzy model and adopting the state feedback parallel distributed compensation structure. , when the actuator fails, the fault-tolerant controller can achieve the maximum wind energy capture below the rated wind speed and the stable operation of the system, but its control is prone to time lag, static deviation exists and the robustness needs to be further improved

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