Input-output Feedback Linearization Control Research Articles

Robust Control for High Performance Induction Motor Drives Based on Partial State-Feedback Linearization

This paper deals with a robust input–output feedback linearization control technique for induction motors. Indeed, classic feedback linearization presents two main disadvantages: 1) the accuracy of the dynamic model; and 2) the corresponding correct knowledge of the model parameters. To address this issue, the linear controller has been substituted with a suitably controller designed to be robust to the variations of the main parameters of the induction motor, like stator and rotor resistances, and the three-phase magnetizing inductance. The proposed controller has been tested both in numerical simulation and experimentally on a suitably designed test setup. Moreover, it has been compared with the classical feedback linearization based on linear controllers, highlighting the improvements in terms of dynamic performance, when parameter variations occur. Results confirm a significant increase of the robustness of the controller against parameter variations.

Real-time Neural Input–Output Feedback Linearization control of DFIG based wind turbines in presence of grid disturbances

This paper proposes a Neural Input–Output Feedback Linearization (N-IOFL) controller for a Doubly Fed Induction Generator (DFIG) prototype connected to the grid. Under unbalanced grid voltages, the existing control strategies need to be modified, becoming very complicated. By using an identifier based on Recurrent High Order Neural Network (RHONN), trained on-line with an Extended Kalman Filter (EKF), an adequate model of the DFIG and of the DC-link can be obtained, which helps the control law based on feedback linearization to reject grid disturbances appearing under non-ideal grid conditions without decomposition process. Based on such identification, the proposed controller is used to track a desired Direct Current (DC) voltage reference at the output of DC-link, to maintain constant the electric power factor controlled by the Grid Side Converter (GSC), and to force independently the rotor currents to track a specified reference defined from the required stator powers, controlled by the Rotor Side Converter (RSC), under both balanced and unbalanced grid conditions. Real-time results illustrate the effectiveness of the proposed controller even in presence of non-ideal grid conditions.

Input-output tracking control of a 2-DOF laboratory helicopter with improved algebraic differential estimation

This paper presents a study on input-output feedback linearization control (OFLC) of a laboratory twin rotor helicopter system based on an improved algebraic differential estimation approach. In the previous algebraic differential estimation studies, the reset time Tr is always selected cautiously in a narrow range because the estimation accuracy is very sensitive to Tr. Too small or too large reset time Tr will lead to an inaccurate estimation of signal derivatives. In this paper, we first propose a new resetting and overlapping strategy for improving the robustness of the estimation algorithm. Then it is used to estimate the velocities of pitch and yaw motions. The OFLC is designed and verified by letting the output signals track different periodic reference signals. Both simulation and experimental results show better control performance as compared with the LQR design.

Neural Input Output Feedback Linearization Control of a DFIG based Wind Turbine

Wind energy has many advantages, because it does not pollute and is an inexhaustible source of energy. The Double Fed Induction Generator (DFIG) is the most important generator used for Horizontal Axis Wind Turbine (HAWT). In this paper, a nonlinear controller is designed based on the Neural Input-Output Feedback Linearization Control ( N-IOFLC) for DFIG, to force the rotor currents to track specified reference defined form the desired active and reactive stator powers, using the fourth order model of the doubly-fed induction machine in (d, q) axis reference frame with stator currents and rotor currents components as state variables. The neural controller is based on a Recurrent High Order Neural Network (RHONN), trained with an Extended Kalman Filter (EKF). The RHONN works as an identifier to obtain an accurate model which is robust to disturbances and parameter variations. The DFIG stator is directly connected to the grid; the rotor is connected via a back to back converter. Computer simulation results obtained, using Matlab/Simulink⋆, confirm the validity and effectiveness of the proposed control approach.

Torque ripple reduction of brushless DC motor based on adaptive input-output feedback linearization

Torque ripple reduction of Brushless DC Motors (BLDCs) is an interesting subject in variable speed AC drives. In this paper at first, a mathematical expression for torque ripple harmonics is obtained. Then for a non-ideal BLDC motor with known harmonic contents of back-EMF, calculation of desired reference current amplitudes, which are required to eliminate some selected harmonics of torque ripple, are reviewed. In order to inject the reference harmonic currents to the motor windings, an Adaptive Input-Output Feedback Linearization (AIOFBL) control is proposed, which generates the reference voltages for three phases voltage source inverter in stationary reference frame. Experimental results are presented to show the capability and validity of the proposed control method and are compared with the vector control in Multi-Reference Frame (MRF) and Pseudo-Vector Control (P-VC) method results.

Dynamics and input–output feedback linearization control of a wheeled mobile cable-driven parallel robot

In comparison to the conventional parallel robots, cable-driven parallel robots (CDPRs) have generally superior features such as simple production technology, low energy consumption, large workspace, high payload to moving weight ratio, and also low cost. On the other hand, a wheeled mobile robot (WMR) which is capable of covering a vast area can be used when no specific space is designated for the stationary accessories of a robot. In this paper, the integration of a CDPR with a WMR is proposed to overcome some of the issues related to each of these robots. The kinematic equations of the robot are presented. To derive the dynamic equations, Gibbs–Appel (G–A) formulation is used, which in contrary to the Lagrange formulation benefits from advantages of quasi-velocities over generalized coordinates as well as not requiring Lagrange multipliers. The dynamic equations of the two parts are coupled, and the interacting effects are observable from the governing equations. By considering non-holonomic wheels for the robot, internal dynamics appears in the equations. However, based on some conditions, the equations are input–output linearizable via a static feedback. The platform trajectory is designed based on the given end-effector trajectory. The effectiveness of the controller is shown through simulations and experimental tests.

IMPROVING THE PERFORMANCE OF WIND TURBINE EQUIPPED WITH DFIG USING STATCOM BASED ON INPUT-OUTPUT FEEDBACK LINEARIZATION CONTROLLER

Using the FACTS controllers, such as static synchronous compensator (STATCOM), as it provides continuous reactive power, in the grid including wind turbine (WT) equipped with doubly fed induction generator, for improving voltage profile (under normal circumstances) and providing a transition ability from inductor generator transition state has been proposed. In this paper, in order to control the controllers and explained goals, nonlinear controller, as a substitute for the traditional controller, is presented. Replacing STATCOM controller in wind farm, which is equipped with doubly fed induction generator (DFIG) using input-output feedback linearization controller, the needed reactive power in order to stable wind farm equipped with DFIG is considered when error is occurred. The proposed control method has been simulated for IEEE-9 Bus, bus No 5, and the achievability to the desired targets in STATCOM efficiency for its reactive power has been investigated. The reasons of using these controllers in bus 5 are voltage dropping and reducing reactive power in this bus. It can be seen by compensating for voltage and reactive power in this bus that these two parameters have improved in other buses. The results show that with the proposed controller, STATCOM has done its duty well and the network bus voltage and reactive power to sustain the wind farm equipped with DFIG in transient mode is provided.

Implementation of sensorless IPMSM drive using the stator current space vector orientation reference frame

Purpose In this paper an adaptive nonlinear control scheme has been proposed for direct torque and flux control of interior permanent magnet synchronous motor (IPMSM) without using mechanical sensor. Design/methodology/approach In this control method the stator resistance is online estimated by adaptive input-output state feedback linearization (AIOFL) controller. Based on proposed control scheme, the strategies of the maximum torque per ampere (MTPA) and maximum power factor (MPF) have been tested using a so-called stator flux search method. Findings The motor equations are transferred from the stationary reference frame to the (SX-SY) two-axis frame of the current by the stator current angle. In this frame, the Y component of the motor current is set to zero and the implementation of the nonlinear controller is independent of the two-axis inductances, the rotor magnetic flux, and position. Practical implications The effectiveness and capability of the proposed control method has been verified by simulation and experimental results. The proposed control scheme can be used for the sensorless control of IPMSM drive in industrial applications such as electric vehicle, traction system, and air conditioner. Originality/value The proposed controller is developed in a special axis (X-Y) rotating reference frame with the X-axis in coincide with the machine current space vector so that there is no need to use and know the machine inductances and rotor position.

Input–Output Feedback Linearization Control With On-Line MRAS-Based Inductor Resistance Estimation of Linear Induction Motors Including the Dynamic End Effects

This paper proposes the theoretical framework and the consequent application of the input–output feedback linearization (FL) control technique to linear induction motors (LIMs). LIM, additionally to rotating induction motor, presents other strong nonlinearities caused by the dynamic end effects, leading to a space-vector dynamic model with time-varying inductance and resistance terms and a braking force term. This paper, starting from a recently developed dynamic model of the LIM taking into consideration its end effects, defines a FL technique suited for LIMs, since it inherently considers its dynamic end effects. Additionally, it proposes a technique for the on-line estimation of the inductor resistance, based on model reference adaptive system (MRAS) on-line estimator; it has been exploited for adapting on-line the FL control action versus inductor resistance variations leading to undesirable steady-state tracking errors. The stability of the proposed MRAS on-line estimator has been proven theoretically, adopting the Popov's criterion for hyperstability. The proposed approach has been validated experimentally on a suitably developed test setup, under both no load and loaded conditions. It has been compared firstly with the simplest control structure, which is the scalar $V/f$ control, secondly under the same closed-loop bandwidths of the flux and speed systems, with the industrial standard in terms of high-performance control technique, i.e., field-oriented control.

Feedback linearization control approach for Brushless Doubly-Fed Machine

This paper presents a novel decoupling control strategy, corresponding to the vector control of induction motors, for the Brushless Doubly-Fed Machine (BDFM). The affine nonlinear state equation of the BDFM within an arbitrary rotating reference frame is also given for the first time. To achieve decoupling control over torque and flux, an input-output feedback linearization control strategy is used. A new control arithmetic, realized in the synchronous reference frame oriented by the control motor rotor flux, is developed. The necessary condition for implementation of the proposed control strategy is demonstrated. Simulation results confirm the feasibility and superb performance of the proposed strategy.

Nonlinear Control of a TiltRotor UAV for Load Transportation

This paper proposes a nonlinear control strategy to solve the suspended load transportation problem using a Tilt-rotor Unmanned Aerial Vehicle. The aim is to maintain both the aircraft and the load stable throughout the whole trajectory, even in the presence of parametric uncertainties and measurement errors. The system modeling is obtained via Euler-Lagrange formulation considering both the dynamics of the Tilt-rotor UAV and the suspended load. A three-level cascade control strategy is proposed. Each level of the cascade system executes an input-output feedback linearization control law. A controller is designed so as to perform path tracking while also avoiding load swing. The solution is compared to a simpler controller whose design considers the load as a disturbance to the system but does not avoid its swing. Simulation results are carried out to corroborate the proposed control strategy.

Input–output feedback linearizing control of linear induction motor taking into consideration the end-effects. Part II: Simulation and experimental results

This is the second part of a paper, divided in two parts, dealing with the application of the input–output feedback linearization (FL) control technique to linear induction motors (LIMs).The first part has treated the theoretical formulation of the input–output feedback linearization control technique as to be applied to linear induction motors. This second part describes the set of tests, both in numerical simulations and experiments, performed to assess the validity of the control technique. In particular, it addresses the issues of the sensitivity of the FL control versus the LIM electrical parameters’ variations and the improvements achievable by considering the LIM dynamic end effects in the control formulation.The proposed FL technique has been further compared, under the same closed-loop bandwidths of the flux and speed systems, with the industrial standard in terms of high performance control technique: field oriented control (FOC).

Control Schemes for a Quadruple Tank Process

This paper deals with the control of a quadruple tank process. A gain scheduling controller, a linear parameter varying controller and an input-output feedback linearization controller are proposed for the quadruple tank process. The derivation of the three control schemes is presented in details. Moreover, the proposed control schemes are implemented using an experimental setup. The experimental results indicate that the developed control schemes work well and are able to regulate the output of the process to its desired value. Additionally, the implementation results demonstrate that the input-output feedback linearization controller gave the best performance.

Speed sensoless robust control of permanent magnet synchronous motor based on second-order sliding-mode observer

This paper is devoted to the study of the performances of a robust speed sensorless nonlinear control of permanent magnet synchronous machine. In the first part, the controllers are designed using two methods: the first one using the input output feedback linearization control and the second is a nonlinear control based on Lyapunov theory combined with sliding mode control. This second solution shows good robustness with respect to parameter variations, measurement errors and noises. In the second part, the high order sliding mode speed observer is used to overcome the occurring chattering phenomena. The super twisting algorithm is modified in order to design a speed and position observer for PMSM. Finally, simulation results are given to demonstrate the effectiveness and the good performance of the proposed control methods.

Damping of Low Frequency Oscillations of Multi-Machine Multi-UPFC Power Systems, Based on Adaptive Input-Output Feedback Linearization Control

In this paper, damping of the low frequency oscillations of multi-machine multi-UPFC power systems is investigated based on adaptive input-output feedback linearization control (AIFLC) approach. Considering a three-phase symmetrical fault, ignoring the subtransient states of the synchronous machines, the nonlinear state equations of the system are derived in order to obtain the UPFC reference control signals as well as the system parameters estimation laws. The stability of the system controller is proved by Lyapunov theory. Moreover using the six reduced order model of synchronous machine, some simulation results are presented in order to verify the validity and effectiveness of the proposed control approach.

REVIEW OF DYNAMICS AND CONTROL OF STRATOSPHERIC AIRSHIPS

The developmental history and research status of airship are briefly presented. Compared with the traditional aircraft, spacecraft, submarines and low altitude airship, the flight principle of stratospheric airships is elaborated. From the point of view of basic motion model and the complex force condition, progresses in dynamics research are discussed systematically, including aerodynamics research, static analysis, thermodynamic analysis, flexible body dynamics and the study of fluid-solid coupling. Then the progress in airship control methods is reviewed, including the small disturbance linearization control, input output feedback linearization control, the Lyapunov nonlinear stability based control and other control method. Finally, it is proposed to reinforce research efforts in six directions in the field of stratospheric airship dynamics and control.

Sensorless fuzzy sliding mode control for permanent magnet synchronous motor fed by AC/DC/AC converter

In this paper a systematic fuzzy sliding mode controller is presented for permanent magnet synchronous motor (PMSM) sensorless drives. The fuzzy sliding mode controller is designed based on input–output feedback linearization control technique. The extended Kalman filter is used to estimate the speed, position and load torque. The PMSM is fed from indirect power electronics converter. This indirect converter is controlled by the sliding mode technique. This control technique allows the minimization of harmonics introduced by the line converter, including the control of power factor and DC-link voltage. The robustness of the overall system is studied using simulation for different operating modes and varied parameters.

Robust DTC Control of Doubly-Fed Induction Machines Based on Input-Output Feedback Linearization Using Recurrent Neural Networks

This paper describes a novel Direct Torque Control (DTC) method for adjustable speed Doubly-Fed Induction Machine (DFIM) drives which is supplied by a two-level Space Vector Modulation (SVM) voltage source inverter (DTC-SVM) in the rotor circuit. The inverter reference voltage vector is obtained by using input-output feedback linearization control and a DFIM model in the stator a-b axes reference frame with stator currents and rotor fluxes as state variables. Moreover, to make this nonlinear controller stable and robust to most varying electrical parameter uncertainties, a two layer recurrent Artificial Neural Network (ANN) is used to estimate a certain function which shows the machine lumped uncertainty. The overall system stability is proved by the Lyapunov theorem. It is shown that the torque and flux tracking errors as well as the updated weights of the ANN are uniformly ultimately bounded. Finally, effectiveness of the proposed control approach is shown by computer simulation results.

Combined Sliding Mode Control with a Feedback Linearization for Speed Control of Induction Motor

Induction Motor (IM) speed control is an area of research that has been in prominence for some time now. In this paper, a nonlinear controller is presented for IM drives. The nonlinear controller is designed based on input-output feedback linearization control technique, combined with sliding mode control (SMC) to obtain a robust, fast and precise control of IM speed. The input-output feedback linearization control decouples the flux control from the speed control and makes the synthesis of linear controllers possible. To validate the performances of the proposed control scheme, we provided a series of simulation results and a comparative study between the performances of the proposed control strategy and those of the feedback linearization control (FLC) schemes. Simulation results show that the proposed control strategy scheme shows better performance than the FLC strategy in the face of system parameters variation.

Input output feedback linearization control and variable step size MPPT algorithm of a grid-connected photovoltaic inverter

In this paper, the power factor of a grid-connected photovoltaic inverter is controlled using the input output Feedback Linearization Control (FLC) technique. This technique transforms the nonlinear state model of the inverter in the d–q reference frame into two equivalent linear subsystems, and then applies a pole placement linear control loops on this subsystem in order to separately control the grid power factor and the dc link voltage of the inverter. Maximum Power Point Tracker (MPPT) that allows extraction of maximum available power from the photovoltaic (PV) array has been included. This MPPT is based on variable step size incremental conductance method. Compared with conventional fixed step size method, the variable step MPPT improves the speed and the accuracy of the tracking.