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The introduction of advanced control algorithms may improve considerably the efficiency of wind turbine systems. This work proposes a high order sliding mode (HOSM) control scheme based on the super twisting algorithm for regulating the wind turbine speed in order to obtain the maximum power from the wind. A robust aerodynamic torque observer, also based on the super twisting algorithm, is included in the control scheme in order to avoid the use of wind speed sensors. The presented robust control scheme ensures good performance under system uncertainties avoiding the chattering problem, which may appear in traditional sliding mode control schemes. The stability analysis of the proposed HOSM observer is provided by means of the Lyapunov stability theory. Experimental results show that the proposed control scheme, based on HOSM controller and observer, provides good performance and that this scheme is robust with respect to system uncertainties and external disturbances.

In this document it is presented and experimentally validated a new linear predictive regulator to control the mechanical speed and the rotor flux of induction motor (IM). The regulator is developed in the synchronous reference frame and it provides a very good dynamic performance and guarantees fulfilment with the current constraints, to avoid over currents in stator windings. This predictive controller employs the minimum necessary dynamic model of the motor to get minor computational cost, in which the rotor flux and the load torque are estimated, and in spite of important parametric uncertainties, the performance is excellent. Moreover, the predictive regulator anticipates the response and compensates the mechanical dead time of the speed induction motor drive, getting better results than the classic speed PI control scheme. This control scheme incorporates the space vector pulse width modulation (SVPWM) with two proportional–integral​ (PI) current controllers, where the rest of dynamics of motor (stator) is controlled and voltage constraints are implemented, ensuring that the modulator always works in the linear area, to prevent distortion in the resulting stator currents. From the experimental tests that have been carried out, it can be concluded that the presented controller provides an effective and robust mechanical velocity and rotor flux tracking, from low to high speed range, with a high accuracy.

In this paper, an enhanced Integral Sliding Mode Control (ISMC) for mechanical speed of an Induction Motor (IM) is presented and experimentally validated. The design of the proposed controller has been done in the d-q synchronous reference frame and indirect Field Oriented Control (FOC). Global asymptotic speed tracking in the presence of model uncertainties and load torque variations has been guaranteed by using an enhanced ISMC surface. Moreover, this controller provides a faster speed convergence rate compared to the conventional ISMC and the Proportional Integral methods, and it eliminates the steady-state error. Furthermore, the chattering phenomenon is reduced by using a switching sigmoid function. The stability of the proposed controller under parameter uncertainties and load disturbances has been provided by using the Lyapunov stability theory. Finally, the performance of this control method is verified through numerical simulations and experimental tests, getting fast dynamics and good robustness for IM drives. The University of the Basque Country (UPV/EHU) [grant number PIF 18/127] has funded the research in this paper

An integral sliding mode control (ISMC) for stator currents of the induction motor (IM) is developed in this work. The proposed controller is developed in the d-q synchronous reference frame, by using the indirect field-oriented control (FOC) method. Robust asymptotic tracking of stator current components in the presence of model uncertainties and current coupling disturbance terms has been guaranteed by using an enhanced ISMC surface. More precisely, the stationary error of stator currents has been eliminated, and the accuracy of the regulators has been enhanced. According to the Lyapunov approach, it has been proven that the stator currents tracking happens asymptotically, and consequently, the stability of each loop has been demonstrated. Simulation and experimental results show the capability of the new controller in diminishing system chattering and increasing the robustness of the designed scheme, considering the variation of the plant parameters and current disturbance terms. It has been illustrated that compared with the conventional ISMC and PI regulators, the proposed current controllers provide smoother control actions and excellent dynamics. In addition, because of the precise control over the rotor flux, the rotor flux weakening method is employed to run the motor at a higher speed than the rated value. The University of the Basque Country (UPV/EHU) [grant number PIF 18/127] has funded the research in this paper.

Oscillating water column (OWC) systems are water power generation plants that transform wave kinetic energy into electrical energy by a surrounded air column in a chamber that changes its pressure through the waves motion. The chamber pressure output spins a Wells turbine that is linked to a doubly fed induction generator (DFIG), flexible devices that adjust the turbine speed to increase the efficiency. However, there are different nonlinearities associated with these systems such as weather conditions, uncertainties, and turbine stalling phenomenon. In this research, a fuzzy logic controller (FLC) combined with an airflow reference generator (ARG) was designed and validated in a simulation environment to display the efficiency enhancement of an OWC system by the regulation of the turbine speed. Results show that the proposed framework not only increased the system output power, but the stalling is also avoided under different pressure profiles. This research was funded by the Basque Government, through the project EKOHEGAZ (ELKARTEK KK-2021/00092), Diputación Foral de Álava (DFA) through the project CONAVANTER, and to the UPV/EHU through the project GIU20/063.

Nowadays, the increase in solar energy installations as a source of energy is growing considerably. The connection to the grid of these installations generally injects all the power obtained from the panel as active power, making zero the reactive power. The same power injection system can be used to achieve a unit power factor if the active filter feature is integrated in it. In this paper, an active power filter (APF) that can control both, the MPP (maximum power point) of a photovoltaic system (PV) and the power factor of a nonlinear load connected to the grid using a three phase DC/AC power inverter with new sliding mode controllers is presented. Perturbation–observation (P&O) is the used MPPT algorithm and three Sliding Mode Controllers (SMC) are used to regulate the DC voltage of the PV and the current d and q components of the active filter using the PQ theory. With a SMC, no exact knowledge of the model parameters is required and it offers good behavior against unmodeled dynamics, insensitivity to parameter variations and good rejection of external disturbances. The space vector pulse wide modulation (SVPWM) of 7 and 5 segments is implemented in order to check the efficiency and grid current ripple. Several experimental tests have been carried in different conditions, concluding that the presented system provides an efficient maximum power tracking and a good power filter characteristic.

This work proposes a robust controller for a variable speed wind turbine system with a doubly feed induction generator. The controller aims at tracking the optimal speed of the wind turbine so that extracts the maximum power from the wind. Also, a robust aerodynamic torque observer is proposed in order to avoid the use of wind speed sensors. This torque observer allows to estimate the aerodynamic torque to be used by the controller in order to calculate the value of the optimal reference speed for the wind turbine. The vector control theory is applied in the present approach, and thereby the stator flux-oriented control is used for controlling the speed of the wind turbine generator. The proposed robust control law is based on sliding mode control theory, which has proved to provide good performance under system uncertainties. The stability of the proposed controller under disturbances and parameter uncertainties has been analyzed using the Lyapunov stability theory. Finally, real time experimental results show that, on the one hand, the proposed controller provides high-performance dynamic characteristics, and on the other hand, this scheme is robust with respect to the uncertainties that usually appear in this kind of systems.

This document studies torque degradation of an internal permanent magnet motor due to an incorrect rotor angle measurement when low rotor angle resolution sensors are used. The performance of the control with different rotor angle resolution is also analysed to determine the torque error due to the use of an incorrect synchronous rotating reference system. To address torque degradation due to the low resolution of Hall sensors, a new method of estimating the rotor angle is proposed that incorporates the information from Hall sensors. In this way, good resolution is achieved, allowing the machine to be controlled over a wide speed range even with rated torque. This method is validated through simulations and real experiments.

In this paper, a generalized predictive control scheme for wind energy conversion systems that consists of a wind turbine and a doubly-fed induction generator is proposed. The design is created by using the maximum power point tracking theory to maximize the extracted wind power, even when the turbine is uncertain or the wind speed varies abruptly. The suggested controller guarantees compliance with current constraints by applying them in the regulator’s conceptual design process to assure that the rotor windings are not damaged due to the over-current. This GPC speed control solves the optimization problem based on the truncated Newton minimization method. Finally, simulation results, which are obtained through the Matlab/Simulink software, show the effectiveness of the proposed speed regulator compared to the widely used Proportional-integral controller for DFIG. The University of the Basque Country (UPV/EHU) (grant number PIF 18/127) has funded the research in this paper.

Wind-generated energy is a fast-growing source of renewable energy use across the world. A dual-feed induction machine (DFIM) employed in wind generators provides active and reactive, dynamic and static energy support. In this document, the droop control system will be applied to adjust the amplitude and frequency of the grid following the guidelines established for the utility&rsquo, s smart network supervisor. The wind generator will work with a maximum deloaded power curve, and depending on the reserved active power to compensate the frequency drift, the limit of the reactive power or the variation of the voltage amplitude will be explained. The aim of this paper is to show that the system presented theoretically works correctly on a real platform. The real-time experiments are presented on a test bench based on a 7.5 kW DFIG from Leroy Somer&rsquo, s commercial machine that is typically used in industrial applications. A synchronous machine that emulates the wind profiles moves the shaft of the DFIG. The amplitude of the microgrid voltage at load variations is improved by regulating the reactive power of the DFIG and this is experimentally proven. The contribution of the active power with the characteristic of the droop control to the load variation is made by means of simulations. Previously, the simulations have been tested with the real system to ensure that the simulations performed faithfully reflect the real system. This is done using a platform based on a real-time interface with the DS1103 from dSPACE.

This paper presents the design and implementation of a supervisory control and data acquisition (SCADA) system for automatic fault detection. The proposed system offers advantages in three areas: the prognostic capacity for preventive and predictive maintenance, improvement in the quality of the machined product and a reduction in breakdown times. The complementary technologies, the Industrial Internet of Things (IIoT) and various machine learning (ML) techniques, are employed with SCADA systems to obtain the objectives. The analysis of different data sources and the replacement of specific digital sensors with analog sensors improve the prognostic capacity for the detection of faults with an undetermined origin. Also presented is an anomaly detection algorithm to foresee failures and to recognize their occurrence even when they do not register as alarms or events. The improvement in machine availability after the implementation of the novel system guarantees the accomplishment of the proposed objectives. This work was supported partially by the Basque Government through project IT1207-19, and by the MCIU/MINECO through RTI2018-094902-B-C21/RTI2018-094902-B-C22 (MCIU/AEI/FEDER, UE). The authors would like to thank Intenance Company for its collaboration and help.

This document presents an efficient proportional derivative (PD) position controller for three-phase motor drives. The regulator has been designed in frequency domain, employing the direct&ndash, quadrature (d&ndash, q) synchronous rotating reference frame and the indirect vector control. The presented position regulator is easy to tune and incorporates a feed forward (FF) term to compensate effectively the effect of the load disturbance. This position controller has been validated experimentally by using two industrial three-phase motors: an induction motor (IM) of 7.5 kW and a permanent magnet synchronous motor (PMSM) of 3.83 kW. The inner proportional integral (PI) current loops of both machines have also been designed in the frequency domain. Each machine has connected in its shaft an incremental encoder of 4096 pulses per revolution, to measure the position. Several simulations and experimental tests have been carried out with both motors, in favorable conditions and also with various types of adversities (parametric uncertainties, unknown load disturbance and measurement noise in the position and current loops), getting very good results and suggesting that this controller could be used in the research area and also in the industry.

Due to the nonlinear dynamics and uncertainties usually present in wave energy conversion systems, the efficiency of these devices can be enhanced employing a robust control algorithms. Wave energy converters are constructed using electric generators of variable velocity, like double feed induction generator (DFIG) since they may improve the system efficiency to generate power when compared to fixed speed generators. The main reason is that this generators with variable speed may adapt the speed of the turbine in order to maintain the optimal flow coefficient values which improves the efficiency of the Wells turbine. However, a suitable speed controller is required in these systems first in order to avoid the stalling phenomenon and second in order to track the optimal turbine reference velocity that optimizes the power generation. In this paper a real time sliding mode control scheme for wave energy conversion systems that incorporate a Wells turbine and a DFIG is proposed. The Lyapunov stability theory is used to analyse the stability of this control scheme under parameter uncertainties and system disturbances. Next, the proposed control scheme is validated first by means of some simulation examples using the Matlab/Simulink software and second using a real-time experimental platform based on a dSPACE DS1103 control board.

This paper presents the design and experimental validation of a new Sliding Mode Controller (SMC) for a single-phase grid-tie inverter in a photovoltaic (PV) Maximum Power Point Tracking (MPPT) application. The number of PV modules required in the string is determined to meet the voltage requirements of the grid-connected inverter, this way the PV modules are connected directly to the DC link of the inverter in a centralized topology and the high step-up power converter of the conventional systems is avoided, obtaining a higher efficiency. The used MPPT algorithm is the hill climbing or perturbation–observation (P&O) and a new Sliding Mode Controller is used to regulate the desired inverter voltage according to the MPPT algorithm. SMC allows to avoid the need of an exact knowledge of the system parameters and offers many desirable properties, such as good performance against no modelled dynamics, insensitivity to parameter variations, and an excellent external disturbance rejection. The inverter control has been designed in the d-q rotating reference frame after use a virtual bi-phase system. Several experimental tests have been carried out in suitable and adverse conditions, concluding that the presented system provides an efficient maximum power tracking.

This document presents the design of an efficient poles placement (RST) position regulator for induction motor drives. The position controller has been designed in d-q synchronous reference frame with indirect vector control or Field Oriented Control (FOC). The presented regulator has been validated experimentally employing an industrial induction motor of 7.5 kW. To compensate the undesirable effect of the load torque on the position tracking, a Feed-Forward (FF) term has been added to the poles placement control term. Several experimental tests have been carried out, getting very good results in favorable conditions and in adverse conditions like unknown load disturbance, uncertainties in parameter and measurement noises in the loop signals. The stability of the controlled system is demonstrated by chosen (placed) discrete poles for the regulated system.

Power generated from wind is a fast growing renewable source of the world energy consumption. A double feed induction generator (DFIG) used in wind turbines, provides dynamic and static active and reactive power support. In this paper, the droop control technique is used to regulate the grid amplitude and frequency according to the criteria defined for the smart grid supervisor. Wind turbine will operate in an unloaded maximum power curve, and according to the reserved active power to correct the frequency deviation, the limit of the reactive power or voltage amplitude correction will be explained. In addition, the offset adjustment of the encoder and the stator synchronization and connection to the grid will be explained. The connection process to the grid and the regulation of a real 7.5kW DFIG is performed controlling the active and reactive powers to their reference values. For that, a platform based on a real-time interface with the DS1103 board is used.

An adaptive robust position control for real-time high-performance applications of induction motors is developed in this work. The proposed sliding-mode controller provides a global asymptotic position tracking in the presence of model uncertainties and load torque variations. The proposed control scheme incorporates an adaptation law for the switching gain, so that the controller can calculate the switching gain value that is necessary to overcome the existing system uncertainties. The design also incorporates a sliding-mode-based load torque and rotor flux observers in order to improve the control performance without using sensors that increase cost and reduce reliability. The proposed design does not present a high computational cost and, therefore, can be easily implemented in real-time applications. Simulated and experimental results show that this scheme provide high-performance dynamic characteristics, and that it is robust with respect to plant parameter variations and external load disturbances.

Robust control algorithms may improve the efficiency of wave power conversion systems since they present intrinsic nonlinear dynamics and the system uncertainties. Sometimes, the generators that can operate al variable speed (e.g. double feed induction generator) are used at wave power generation plants, since they may improve the system efficiency to generate power when compared to fixed speed generators. The main reason is that this generators with variable speed may adapt the speed of the turbine in order to maintain the optimun flow coefficient value which improving its efficiency. This paper proposes a sliding mode controller for wave power plants based on a double feed induction generator. Also, the presented robust control scheme introduces an adaptive sliding gain that avoids calculating the upper bound for the uncertainties of the system, facilitating its application. The stability of the proposed control scheme is analyzed by means of the Lyapunov stability theory. Finally, the proposed control scheme is validated through some simulation examples.

In this paper a sliding mode position control for high-performance real-time applications of induction motors is developed. The design also incorporates a sliding mode rotor flux estimator in order to avoid the flux sensors. The proposed control scheme presents a low computational cost and therefore can be implemented easily in a real-time applications using a low cost Digital Signal Processor (DSP). The stability analysis of the observer and the controller, under parameter uncertainties and load torque disturbances, is provided using the Lyapunov stability theory. Finally simulated and experimental results show that the proposed controller with the proposed observer provides a good trajectory tracking and that this scheme is robust with respect to plant parameter variations and external load disturbances.

This paper presents an effective Proportional Derivative (PD) position controller of induction motor drives. A new procedure for controller design in frequency domain and the d-q synchronous rotating reference frame is presented, where the indirect vector control has been used. This position controller is validated experimentally using an industrial induction motor of 7.5 kW and an incremental encoder of 4096 impulses per revolution. The position regulator includes an effective FeedForward (FF) term instead of the Integral action (I), reducing drastically the undesirable effect of the unknown load disturbance on the position tracking. The presented algorithm has been tested using several simulation and real experiments, in suitable conditions and also in adverse conditions employing the unknown load disturbance, parameter uncertainties and measurement noise in the position and stator current loops signals, where its functional robustness is clearly demonstated. The obtained results are very satisfactory, suggesting its use in industry and in the research area to be used as a reference with other advanced position regulators. The stability of the controlled system is demonstrated in frequency domain and also by discretization of poles.

A novel adaptive sliding-mode control system is proposed in order to control the speed of an induction motor drive. This design employs the so-called vector (or field oriented) control theory for the induction motor drives. The sliding-mode control is insensitive to uncertainties and presents an adaptive switching gain to relax the requirement for the bound of these uncertainties. The switching gain is adapted using a simple algorithm which does not imply a high computational load. Stability analysis based on Lyapunov theory is also performed in order to guarantee the closed loop stability. Finally, simulation results show not only that the proposed controller provides high-performance dynamic characteristics, but also that this scheme is robust with respect to plant parameter variations and external load disturbances.

This paper presents a new adaptive robust control for induction motor drives. The proposed control scheme is based on the so-called field oriented control theory that allows to control the induction motor like a separately excited direct current motor drive, where the field flux (produced by the field current) and the armature flux (produced by the armature current) are decoupled. The robust control law is based on the sliding mode control theory, but unlike the traditional sliding mode control schemes, the proposed design incorporates an adaptive switching gain that avoids the need of calculating an upper limit of the system uncertainties. Moreover the proposed control law is smoothed out in order to avoid the high control activity inherent to the switching control laws. The resulting closed loop system is proven to be stable using the Lyapunov stability theory. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

A sliding mode position control for high-performance real-time applications of induction motors is developed in this work. The design also incorporates a sliding mode based flux and load torque observers in order to avoid this sensors, that increases the cost and reduces the reliability. Additionally, the proposed control scheme presents a low computational cost and therefore can be implemented easily in a real-time applications using a low cost DSP-processor. The stability analysis of the controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally simulated and experimental results show that the proposed controller with the proposed observer provides a good trajectory tracking and that this scheme is robust with respect to plant parameter variations and external load disturbances.

A robust position control for induction motors using sliding mode observers and controller is proposed. The proposed control scheme incorporates a sliding mode based flux and load torque estimator in order to avoid these sensors, that increases the cost and reduces the system reliability. The proposed control scheme presents a robust performance under system uncertainties and external load torque disturbances. Additionally, the proposed control scheme does not present a high computational cost and therefore can be implemented easily in high-performance real time applications for induction motors.

An adaptive sliding mode position control for induction motors using field oriented control theory is presented. The proposed sliding-mode control law incorporates an adaptive switching gain to avoid calculating an upper limit of the system uncertainties. The design incorporates a flux estimator that operates on the principle of flux and current observer. The proposed observer is basically an estimator that uses a plant model and a feedback loop with measured stator voltages and currents. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally experimental results show that the proposed controller with the proposed observer provides high-performance dynamic characteristics and that this scheme is robust with respect to plant parameter variations and external load disturbances.

14 p. This paper presents and validates a new proposal for effective speed vector control of induction motors based on linear Generalized Predictive Control (GPC) law. The presented GPC-PI cascade configuration simplifies the design with regard to GPC-GPC cascade configuration, maintaining the advantages of the predictive control algorithm. The robust stability of the closed loop system is demonstrated by the poles placement method for several typical cases of uncertainties in induction motors. The controller has been tested using several simulations and experiments and has been compared with Proportional Integral Derivative (PID) and Sliding Mode (SM) control schemes, obtaining outstanding results in speed tracking even in the presence of parameter uncertainties, unknown load disturbance, and measurement noise in the loop signals, suggesting its use in industrial applications. The authors are very grateful to the UPV/EHU for its support throughout the project GUI07/08 and the Basque Government for the support to this work throughout the project S-PE09UN12

Power generated from wind is a fast growing renewable source of the world energy consumption. A test bench for comprehensive research on the doubly fed induction generator (DFIG) used as wind turbine is implemented. The wind energy is emulated with a synchronous machine according to the wind profile specified in the computer. Two inverters in a back to back configuration between the rotor and the grid are used to control the DFIG. The space vector pulse width modulation (SVPWM) technique is used in both inverters. Special attention has been placed in the offset adjustment of the encoder and the stator synchronization and connection to the grid. Finally, the regulation of the DFIG is performed controlling the active and reactive power to their reference values.

This paper presents and validates an efficient position control scheme based on the GPC (Generalized Predictive Control) algorithm for the indirect vector control of the induction motor. The position loop is regulated with a linear GPC controller and the current loops incorporate the SVPWM (Space Vector PWM) with the PI (Proportional Integral) controllers. The presented GPC position control scheme for induction motor provides a low computation cost in respect to the standard GPC algorithm, a fast response and good rejection of uncertainties and measurement noises. This position scheme has been tested using various simulations and experimental tests, with and without unknown load, taking into account the parameter uncertainties and measurement noise in the loop signal, the rotor position and the stator current. This robust position GPC algorithm provides an electromagnetic torque without the undesirable chattering phenomenon.

This paper presents and validates an efficient speed control scheme based on the GPC (Generalized Predictive Control) algorithm for the indirect vector control of the induction motor. The GPC controller is employed in the speed loop, while the current loops incorporate the SVPWM (Space Vector Pulse Width Modulation) with the PI (Proportional Integral) controllers. This GPC speed control scheme for induction motor is based in the TNC (Truncated Newton bound Constrained) minimization method and provides a medium-low computation cost, a fast response and good rejection of uncertainties and measurement noises. The presented speed control algorithm has been tested using various simulation and experimental tests, taking into account the parameter uncertainties and measurement noise in the two loop signals, the rotor speed and the stator current, with and without unknown external load disturbance. This work shows that this robust speed GPC algorithm provides an electromagnetic torque without undesirable chattering phenomenon.

This paper presents and validates an efficient speed control scheme based on the GPC (Generalized Predictive Control) algorithm for the indirect vector control of the induction motor. A linear simplified GPC controller is employed in the speed loop, while the current loops incorporate the SVPWM (Space Vector Pulse Width Modulation) with the PI (Proportional Integral) controllers. The presented GPC speed control scheme for induction motor provides a low computation cost respect the standard GPC algorithm, a fast response and good rejection of uncertainties and measurement noises. This speed control algorithm has been tested using various simulation and experimental tests, with and without unknown external load disturbance, taking into account the parameter uncertainties and measurement noise in the two loop signals, the rotor speed and the stator current. All proofs realized show that this robust speed GPC algorithm provides an electromagnetic torque without undesirable chattering phenomenon.

An adaptive sliding mode position control for induction motors using field oriented control theory is presented. The proposed controller provides global asymptotic position tracking in the presence of unknown parameters and load torque variations. The proposed design incorporates an improved method of flux estimation that operates on the principle of flux and current observer. The proposed observer is basically an estimator that uses a plant model and a feedback loop with measured stator voltages and currents. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory.

The efficiency of the wind power conversions systems can be greatly improved using an appropriate control algorithm. In this work, a robust control for variable speed wind power generation that incorporates a doubly feed induction generator is described. In the presented design it is applied the so called vector control theory. The proposed control scheme uses stator flux-oriented control for the rotor side converter bridge control and grid voltage vector control for the grid side converter bridge control. The proposed robust control law is based on a sliding mode control theory, that, as it is well known, presents a good performance under system uncertainties. The stability analysis of the proposed controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. Finally simulated results show, on the one hand that the proposed controller provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to the uncertainties that usually appear in the real systems.