Robust SVM-direct torque control of induction motor based on sliding mode controller and sliding mode observer

This paper proposes a design of control and estimation strategy for induction motor based on the variable structure approach. It describes a coupling of sliding mode direct torque control (DTC) with sliding mode flux and speed observer. This algorithm uses direct torque control basics and the sliding mode approach. A robust electromagnetic torque and flux controllers are designed to overcome the conventional SVM-DTC drawbacks and to ensure fast response and full reference tracking with desired dynamic behavior and low ripple level. The sliding mode controller is used to generate reference voltages in stationary frame and give them to the controlled motor after modulation by a space vector modulation (SVM) inverter. The second aim of this paper is to design a sliding mode speed/flux observer which can improve the control performances by using a sensorless algorithm to get an accurate estimation, and consequently, increase the reliability of the system and decrease the cost of using sensors. The effectiveness of the whole composed control algorithm is investigated in different robustness tests with simulation using Matlab/Simulink and verified by real time experimental implementation based on dS pace 1104 board.     

Simulating Feedback Linearization control of wind turbines using high‐order models

As wind turbines are becoming larger, wind turbine control must now encompass load control objectives as well as power and speed control to achieve a low cost of energy. Due to the inherent non‐linearities in a wind turbine system, the use of non‐linear model‐based controllers has the potential to increase control performance. A non‐linear feedback linearization controller with an Extended Kalman Filter is successfully used to control a FAST model of the controls advanced research turbine with active blade, tower and drive‐train dynamics in above rated wind conditions. The controller exhibits reductions in low speed shaft fatigue damage equivalent loads, power regulation and speed regulation when compared to a Gain Scheduled Proportional Integral controller, designed for speed regulation alone. The feedback linearization controller shows better rotor speed regulation than a Linear Quadratic Regulator (LQR) at close to rated wind speeds, but poorer rotor speed regulation at higher wind speeds. This is due to modeling inaccuracies and the addition of unmodeled dynamics during simulation. Similar performance between the feedback linearization controller and the LQR in reducing drive‐train fatigue damage and power regulation is observed. Improvements in control performance may be achieved through increasing the accuracy of the non‐linear model used for controller design. Copyright © 2009 John Wiley & Sons, Ltd.     

Robust gain scheduling baseline controller for floating offshore wind turbines

The possibility of a pitch instability for floating wind turbines, due to the blade‐pitch controller, has been discussed extensively in recent years. Contrary to many advanced multi‐input‐multi‐output controllers that have been proposed, this paper aims at a standard proportional‐integral type, only feeding back the rotor speed error. The advantage of this controller is its standard layout, equal to onshore turbines, and the clearly defined model‐based control design procedure, which can be fully automated. It is more robust than most advanced controllers because it does not require additional signals of the floating platform, which make controllers often sensitive to unmodeled dynamics. For the design of this controller, a tailored linearized coupled dynamic model of reduced order is used with a detailed representation of the hydrodynamic viscous drag. The stability margin is the main design criterion at each wind speed. This results in a gain scheduling function, which looks fundamentally different than the one of onshore turbines. The model‐based controller design process has been automated, dependent only on a given stability margin. In spite of the simple structure, the results show that the controller performance satisfies common design requirements of wind turbines, which is confirmed by a model of higher fidelity than the controller design model. The controller performance is compared against an advanced controller and the fixed‐bottom version of the same turbine, indicating clearly the different challenges of floating wind control and possible remedies.     

Model‐based receding horizon control of wind farms for secondary frequency regulation

In this study, we propose the use of model‐based receding horizon control to enable a wind farm to provide secondary frequency regulation for a power grid. The controller is built by first proposing a time‐varying one‐dimensional wake model, which is validated against large eddy simulations of a wind farm at startup. This wake model is then used as a plant model for a closed‐loop receding horizon controller that uses wind speed measurements at each turbine as feedback. The control method is tested in large eddy simulations with actuator disk wind turbine models representing an 84‐turbine wind farm that aims to track sample frequency regulation reference signals spanning 40 min time intervals. This type of control generally requires wind turbines to reduce their power set points or curtail wind power output (derate the power output) by the same amount as the maximum upward variation in power level required by the reference signal. However, our control approach provides good tracking performance in the test system considered with only a 4% derate for a regulation signal with an 8% maximum upward variation. This performance improvement has the potential to reduce the opportunity cost associated with lost revenue in the bulk power market that is typically associated with providing frequency regulation services. Copyright © 2017 John Wiley & Sons, Ltd.     

Mode decomposition approach in robust control design for horizontal axis wind turbines

A robust multivariable strategy for pitch and torque control design of variable‐speed variable‐pitch wind turbines in the full load region is introduced in this paper. The pitch and torque control loops that share the tracking and active damping of drivetrain torsional mode objectives are designed simultaneously using a novel decomposition scheme. This permits the systematic design of robust multivariable controllers for wind turbines in a manner that facilitates industrial application. We achieve this by making the process of weighting function design fast, intuitive, and simple and by giving the designer a clear insight on the compromising aspects of the various control system objectives. FAST simulation is used to demonstrate application of the method.     

Preview predictive control layer design based upon known wind turbine blade‐pitch controllers

The use of upstream wind measurements has motivated the development of blade‐pitch preview controllers for improving rotor speed tracking and structural load reduction beyond that achievable via conventional feedback control. Such preview controllers, typically based upon model predictive control (MPC) for its constraint handling properties, alter the closed‐loop dynamics of the existing blade‐pitch feedback control system. This can result in a deterioration of the robustness properties and performance of the existing feedback control system. Furthermore, performance gains from utilising the upcoming real‐time measurements cannot be easily distinguished from the feedback control, making it difficult to formulate a clear business case for the use of preview control. Therefore, the aim of this work is to formulate a modular MPC layer on top of a given output‐feedback blade‐pitch controller, with a view to retaining the closed‐loop robustness and frequency‐domain performance of the latter. The separate nature of the proposed controller structure enables clear and transparent quantification of the benefits gained by using preview control, beyond that of the underlying feedback controller. This is illustrated by results obtained from high‐fidelity closed‐loop turbine simulations, showing the proposed control scheme incorporating knowledge of the oncoming wind and constraints achieved significant 43% and 30% reductions in the rotor speed and flap‐wise blade moment standard deviations, respectively. Additionally, the chance of constraint violations on the rotor speed decreased remarkably from 2.15% to 0.01%, compared to the nominal controller. Copyright © 2017 John Wiley & Sons, Ltd.     

Multivariable control strategy for variable speed, variable pitch wind turbines

Reliable and powerful control strategies are needed for wind energy conversion systems to achieve maximum performance. A new control strategy for a variable speed, variable pitch wind turbine is proposed in this paper for the above-rated power operating condition. This multivariable control strategy is realized by combining a nonlinear dynamic state feedback torque control strategy with a linear control strategy for blade pitch angle. A comparison with existing strategies, PID and LQG controllers, is performed. The proposed approach results in better power regulation. The new control strategy has been validated using an aeroelastic wind turbine simulator developed by NREL for a high turbulence wind condition.     

Structural load mitigation control for wind turbines: A new performance measure

Structural loads of wind turbines are becoming critical because of the growing size of wind turbines in combination with the required dynamic output demands. Wind turbine tower and blades are therefore affected by structural loads. To mitigate the loads while maintaining other desired conditions such as the optimization of power generated or the regulation of rotor speed, advanced control schemes have been developed during the last decade. However, conflict and trade‐off between structural load reduction capacity of the controllers and other goals arise; when trying to reduce the structural loads, the power production or regulation performance may be also reduced. Suitable measures are needed when designing controllers to evaluate the control performance with respect to the conflicting control goals. Existing measures for structural loads only consider the loads without referring to the relationship between loads and other control performance aspects. In this contribution, the conflicts are clearly defined and expressed to evaluate the effectiveness of control methods by introducing novel measures. New measures considering structural loads, power production, and regulation to prove the control performance and to formulate criteria for controller design are proposed. The proposed measures allow graphical illustration and numerical criteria describing conflicting control goals and the relationship between goals. Two control approaches for wind turbines, PI and observer‐based state feedback, are defined and used to illustrate and to compare the newly introduced measures. The results are obtained by simulation using Fatigue, Aerodynamics, Structures, and Turbulence (FAST) tool, developed by the National Renewable Energy Laboratory (NREL), USA.     

The Design of closed loop controllers for wind turbines

This article reviews the design of algorithms for wind turbine pitch control and also for generator torque control in the case of variable speed turbines. Some recent and possible future developments are discussed. Although pitch control is used primarily to limit power in high winds, it also has a significant effect on various loads. Particularly as turbines become larger, there is increasing interest in designing controllers to mitigate loads as far as possible. Torque control in variable speed turbines is used primarily to maximize energy capture below rated wind speed and to limit the torque above rated. Once again there are opportunities for designing these controllers so as to mitigate certain loads. In addition to improving the design of the control algorithms, it is also possible to use additional sensors to help the controller to achieve its objectives more effectively. The use of additional actuators in the form of individual pitch controllers for each blade is also discussed. It is important to be able to quantify the benefits of any new controller. Although computer simulations are useful, field trials are also vital. The variability of the real wind means that particular care is needed in the design of the trials. Copyright © 2001 John Wiley & Sons, Ltd.     

Identification in closed‐loop operation of models for collective pitch robust controller design

To achieve load reduction and power optimization, wind turbine controllers design requires the availability of reliable control‐oriented linear models. These are needed for model‐based controller design. Model identification of wind turbine while operating in closed loop is an appropriate solution that has recently shown its capabilities when linear time‐invariant controllers and complicated control structures are present. However, the collective pitch control loop, one of the most important wind turbine loops, uses non‐linear controllers. Typically, this non‐linear controller is a combination of a linear controller and a gain scheduling. This paper presents a new algorithm for identification in closed‐loop operation that allows the use of this kind of non‐linear controllers. The algorithm is applied for identification the collective pitch demand to generator speed of a wind turbine at various operating points. The obtained models are presented and discussed from a control point of view. The validity of these models is illustrated by their use for the design of a linear fix robust controller. The performance based on simulation data of this linear controller is similar to that obtained with simulations based on a linear controller with gain scheduling, but its design and implementation is much simpler. Copyright © 2012 John Wiley & Sons, Ltd.     

Predictive control of an experimental wind turbine using preview wind speed measurements

The development of a more reliable method of measuring the wind field upstream of a turbine (light detection and ranging) has enabled the implementation of feedforward‐related control strategies to enhance the control performance of wind turbines. By incorporating wind speed measurements, the controller is able to anticipate upon future events and thereby improve structural load mitigation and power regulation of the wind turbine. This work aims to experimentally verify the benefits of using predictive and feedforward‐based control strategies over industry standard control solutions. To achieve this, both a feedforward and a model predictive control strategy are presented, which have been validated on an experimental wind turbine in a wind tunnel. Both the model predictive controller and feedforward algorithm have shown superior performance over a baseline controller in terms of rotor speed regulation under wind speed disturbances. The experiment confirmed that a phase advantage in the control input of the predictive controller led to this performance increase. It has also been found that knowledge of just the current wind speed can already significantly increase the control performance. Copyright © 2014 John Wiley & Sons, Ltd.     

基于自适应非奇异智能终端滑模观测器的风力机载荷增广预测控制

为有效降低风力机在高风速运行时的不平衡载荷,提出一种基于自适应非奇异智能终端滑模观测器的载荷增广预测控制策略。首先,针对模型不匹配导致的模型预测控制性能下降的问题,将指令跟踪误差与系统状态的变化量增广为状态向量,设计增广预测模型以消除稳态跟踪误差;其次,设计自适应非奇异终端滑模观测器对系统状态进行估计,以提高控制系统的可靠性;然后,设计多目标变速灰狼优化算法同时对控制器和观测器参数寻优;最后,基于Simulink仿真平台验证了所提控制策略的有效性。结果表明,所提控制策略可有效消除稳态误差,缩短调节时间并提高控制性能。     

On-line designed hybrid controller with adaptive observer for variable-speed wind generation system

This paper presents a wind-driven induction generator system with a hybrid controller, which combines the advantages of the integral–proportional and the sliding mode controllers. The proposed controller is designed to adjust the turbine speed to extract maximum power from the wind. The integral–proportional speed controller can be designed on-line according to the estimated rotor parameters, and the observed disturbance torque is feed-forward to increase the robustness of the system. The designed integral switching surface with integral–proportional due to on-line tuning produced a new sliding surface to implement the control, and can ensure the robustness under noisy environment. The rotor inertia constant, friction constant, and the disturbed mechanical torque of the induction generator are estimated by a proposed adaptive observer, which is composed of the recursive least square algorithm and a torque observer.     

A low‐order model for analysing effects of blade fatigue load control

A new low‐order mathematical model is introduced to analyse blade dynamics and blade load‐reducing control strategies for wind turbines. The model consists of a typical wing section model combined with a rotor speed model, leading to four structural degrees of freedom (flapwise, edgewise and torsional blade oscillations and rotor speed). The aerodynamics is described by an unsteady aerodynamic model. The equations of motion are derived in non‐linear and linear form. The linear equations of motion are used for stability analysis and control design. The non‐linear equations of motion are used for time simulations to evaluate control performance. The stability analysis shows that the model is capable of predicting classical flutter and stall‐induced vibrations. The results from the stability analysis are compared with known results, showing good agreement. The model is used to compare the performance of one proportional–integral–derivative controller and two full‐state feedback controllers. Copyright © 2006 John Wiley & Sons, Ltd.     

Linear models‐based LPV modelling and control for wind turbines

The non‐linear behaviour of wind turbines demands control strategies that guarantee the robustness of the closed‐loop system. Linear parameter‐varying (LPV) controllers adapt their dynamics to the system operating points, and the robustness of the closed loop is guaranteed in the controller design process. An LPV collective pitch controller has been developed within this work to regulate the generator speed in the above rated power production control zone. The performance of this LPV controller has been compared with two baseline control strategies previously designed, on the basis of classical gain scheduling methods and linear time‐invariant robust H_∞ controllers. The synthesis of the LPV controller is based on the solution of a linear matrix inequalities system, proposed in a mixed‐sensitivity control scenario where not only weight functions are used but also an LPV model of the wind turbine is necessary. As a contribution, the LPV model used is derived from a family of linear models extracted from the linearization process of the wind turbine non‐linear model. The offshore wind turbine of 5 MW defined in the Upwind European project is the used reference non‐linear model, and it has been modelled using the GH Bladed 4.0 software package. The designed LPV controller has been validated in GH Bladed, and an exhaustive analysis has been carried out to calculate fatigue load reductions on wind turbine components, as well as to analyse the load mitigation in some extreme cases. Copyright © 2014 John Wiley & Sons, Ltd.     

Model predictive control of a wind turbine using short‐term wind field predictions

As wind turbines become larger and hence more flexible, the design of advanced controllers to mitigate fatigue damage and optimise power capture is becoming increasingly important. The majority of the existing literature focuses on feedback controllers that use measurements from the turbine itself and possibly an estimate or measurement of the current local wind profile. This work investigates a predictive controller that can use short‐term predictions about the approaching wind field to improve performance by compensating for measurement and actuation delays. Simulations are carried out using the FAST aeroelastic design code modelling the NREL 5 MW reference turbine, and controllers are designed for both above rated and below rated wind conditions using model predictive control. Tests are conducted in various wind conditions and with different future wind information available. It is shown that in above rated wind conditions, significant fatigue load reductions are possible compared with a controller that knows only the current wind profile. However, this is very much dependent on the speed of the pitch actuator response and the wind conditions. In below rated wind conditions, the goals of power capture and fatigue load control were considered separately. It was found that power capture could only be improved using wind predictions if the wind speed changed rapidly during the simulation and that fatigue loads were not consistently reduced when wind predictions were available, indicating that wind predictions are of limited benefit in below rated wind conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Doubly-fed induction generator drive based WECS using fuzzy logic controller

The purpose of this paper is to improve the control performance of the variable speed, constant frequency doubly-fed induction generator in the wind turbine generation system by using fuzzy logic controllers. The control of the rotor-side converter is realized by stator flux oriented control, whereas the control of the grid-side converter is performed by a control strategy based on grid voltage orientation to maintain the DC-link voltage stability. An intelligent fuzzy inference system is proposed as an alternative of the conventional proportional and integral (PI) controller to overcome any disturbance, such as fast wind speed variation, short grid voltage fault, parameter variations and so on. Five fuzzy logic controllers are used in the rotor side converter (RSC) for maximum power point tracking (MPPT) algorithm, active and reactive power control loops, and another two fuzzy logic controllers for direct and quadratic rotor currents components control loops. The performances have been tested on 1.5 MW doubly-fed induction generator (DFIG) in a Matlab/Simulink software environment.     

Energy capture by a small wind-energy conversion system

Furling is the most common method used by the small wind-turbine industry to control the aerodynamic power extraction from the wind. A small wind-turbine with furling mechanism and its resulting dynamics are modelled using Matlab/Simulinkplatform in this paper. The model simulates regulating the speed of the wind-turbine via a load-control method. Tip-speed ratio and hill-climbing control methods for maximum-power extraction from a small wind-turbine are investigated. Two dynamic controllers are designed and their behaviours simulated. In the first method, the controller uses the wind-speed and rotor speed information to control the load in order to operate the wind-turbine at its optimal tip-speed ratio. In the second method, the controller compares the output power of the turbine with the previous power, and controls the load based on the power difference. In order to determine a suitable control strategy for the small wind-energy conversion system, several tests are performed. Wind-speed versus power-curve and annual energy capture of the system for each control method are determined for wind conditions in St. John’s, Newfoundland. The annual energy-capture is determined using the bin’s power-curve method. Wind-speed data and Rayleigh distribution of St. John’s, Newfoundland are used to determine the annual energy-capture. The results of the simulations indicate that the energy capture of a wind-turbine depends not only on the control strategy but on the wind-speed and Rayleigh distribution. The results of the investigation lead to the conclusion that the hill-climbing method of control results in a greater annual energy-output.     

永磁直驱风力发电机自抗扰技术及其无位置传感器控制策略

针对永磁直驱风力发电机传统矢量控制动态性能差,抗扰动能力弱的问题,提出一种双环线性自抗扰控制系统。在此基础上针对传统滑模观测器抖振等因素造成的速度和位置角观测误差较大的问题,提出改进型自适应滑模观测器。结果表明所设计的速度和电流双环线性自抗扰控制策略能有效提高转速跟踪性能和电流波形质量;在滑模观测器的基础上结合自适应算法精确观测反电动势,借鉴锁相环原理代替反正切函数估算出转子转速和位置角,相比传统滑模观测器具有更高的估算精度。     

Dynamical sliding mode power control of wind driven inductiongenerators

This paper concerns power regulation of variable-speed wind energy conversion systems. These systems have two regions of operation, depending on the tip speed ratio of the wind turbines. They are distinguished by a minimum phase behavior in one of these regions and a nonminimum phase one in the other. A sliding mode control strategy is proposed that assures stability in both regions of operation and imposes the ideally designed feedback control solution in spite of model uncertainties. Moreover, power regulation by the proposed sliding control in the minimum phase region is completely robust to wind disturbances and parameter uncertainties