A Resilient Current Sensor Fault-Tolerant Strategy for Vector-Controlled Induction Motor Drive

In this paper we propose a multisensor switching strategy for fault tolerant control of rotor wound induction motors operating as stand alone generators. The proposed strategy combines three current sensors and associated observers that estimate the stator flux. The estimates provided by the observers are compared at each sampling time by a switching mechanism, which selects the sensors-observer pair with the smallest error between the estimated flux magnitude and a desired flux reference. The estimates provided by the selected pair are used to implement a vector control law. The switching selection is such that measurements from faulty current sensors are automatically avoided by the switching mechanism, thus maintaining good performance levels even in the presence of a faulty sensor. Simulation results under realistic conditions illustrate the effectiveness of the scheme.

This paper presents an application of a sensor fault tolerant control (FTC) scheme on a flexible joint and flexible link. A linear observer is used to reconstruct the faults. Then the reconstruction is subtracted from the faulty sensors to form a `virtual sensor' and this signal (instead of the normally used faulty output) is then used to generate the control input. This minimizes performance degradation. A design method to make the virtual sensor insensitive to system uncertainties is presented. Two fault conditions are tested; total failure and incipient faults. Then the robustness is tested by implementing the joint's FTC scheme on the link. Excellent results have been obtained for both cases; the FTC scheme caused the system performance is almost identical to the fault-free scenario, even for simultaneous faults.

This paper is an attempt to develop an Induction Motor Drive System with Multilevel Inverter topology for reduced torque ripple application. A Nine level-cascaded multilevel inverter is developed for the induction motor drive with SVPWM control powered by boost converter fed using solar PV supply. The SVPWM control based implementation of vector control using a multilevel inverter topology needs a multilevel SVPWM control technique, which is implemented in this paper. The Solar power supplied is applied with the MPPT technique and the supplied DC power is fed to the three phase cascaded 9 level multilevel inverter. The vector control of induction motor is carried out using the SVPWM technique on the multilevel topology. The torque ripple reduction in the output is observed and compared with the vector control of induction motor. Matlab based implementation is carried out and the results are tabulated and inferred.

An effective fault detection and fault tolerant control strategy in induction motor is described in this paper. Based on the algorithm of posterior reliability voting, the proposed approach could detect the healthy state of encoder, and adjust the weights between the speed from encoder and estimated speed based on MRAS. When redundant current sensors are installed in the controller, a logic decision scheme could detect and shield the faulty one, and guarantee that the current signals involved in the control are from the two healthy current sensors. Abrupt faults of both encoder and speed sensor are simulated in the induction motor driver individually, and simulation results in terms of speed response indicate the effectiveness of the proposed strategy subject to faulty conditions caused by encoder or current sensor.

Use of induction motor (IM) at it's highest efficiency is a big demanding task because of their complex mathematical model and non linear features during saturation. These elements make the control of IM strenuous and call for the use of high performance control algorithm such as field orientation control. This paper introduces a speed controller, particularly at minimum speeds by utilizing Fuzzy logic controller (FLC) for indirect field-oriented control (IFOC) of induction motor (IM) drives fed by a four-switch three-phase (FSTP) inverter. From suggested viewpoint, the IM drive is used with a FSTP inverter as an alternative for the conventional six-switch three-phase (SSTP) inverter. Utter IFOC programme includes the FLC of IM drives with the suggested FSTP inverter is raised in MATLAB/Simulink. By considering the good dynamic performance, cost minimization and low total harmonic distortion (THD), FSTP inverters are comparable with SSTP inverters. The dynamic performance and robustness of proposed FLC with the FSTP inverter fed IM drive is verified with PI controller. It is established that the suggested FLC is further powerful than the PI controller under speed tracking and load disturbances

This paper discusses the design of an active fault-tolerant flight control strategy for improvement of the operational control capability of the aircraft system. The research work draws expertise from actions undertaken within the European Flight Mechanics Action Group [FM-AG(16)] on fault-tolerant control, which develops a collaborative effort in Europe to create new fault-tolerant control technologies that significantly advance the goals of the aviation safety. The methodology is applied to a trimmable horizontal stabilizer runaway fault occurring in a large transport aircraft. The goal is to provide a self-repairing capability to enable the pilot to land the aircraft safely. The fault-tolerant control strategy works in such a way that once the fault is detected by the fault detection and isolation unit, a compensation loop is activated for safe recovery. A key feature of the proposed strategy is that the design of the fault-tolerant control loop is done independently of the nominal autopilot and the nominal flight control system in place. Nonlinear simulation results demonstrate the effectiveness of the proposed fault-tolerant control scheme.

The paper introduces a novel Fault Tolerant Control (FTC) algorithm based on estimated stator currents to diagnose some faulty states of stator current and speed sensors of Induction Motor (IM) drives. The FTC unit is integrated in the field-oriented control of induction motors to ensure that the IM drive can operate stably when current and speed sensor failures occur. The presented scheme combines two stator current estimators and a rotor speed estimator where a correction coefficient determined from the healthy current sensor is used to enhance the accuracy of the stator current estimation. To verify the capability of the proposed approach, the simulation in MATLAB-Simulink has been accomplished for various conditions of the IM drive, i.e. normal speed, low speed, and very low speed operating ranges. The results have confirmed very good features of the proposed FTC against the current and speed sensor fault in the different speed ranges.

This research is concerned with the adaptive neural network observer based fault approximation and fault-tolerant control of time-varying nonlinear systems. A new strategy for adaptively updating the weights of neural network parameters is proposed to enhance fault detection accuracy. Lyapunov function theory (LFT) is applied for adaptively updating the learning parameters weights of multi-layer neural network (MLNN). The purpose of using adaptive learning rates to update the weight parameters of MLNN is to obtain the global minima for highly nonlinear functions without increasing the computational complexities and costs and increase the efficacy of fault detection. Results of the proposed adaptive MLNN observer are compared with conventional MLNN observer and high gain observer. The effects of various faults or failures are studied in detail. The proposed strategy shows more robustness to disturbances, uncertainties, and unmodelled system dynamics compared to the conventional neural network, high gain observer and other existing techniques in literature. Fault tolerant control (FTC) schemes are also proposed to account for the presence of various faults and failures. Separate sliding mode control (SMC) based FTC schemes are designed for each observer to ensure stability of the faulty system. The suggested strategy is validated on Boeing 747 100/200 aircraft. Results demonstrate the effectiveness of both the proposed adaptive MLNN observer and the FTC based on the proposed adaptive MLNN compared to the conventional MLNN, high gain observer and other existing schemes in literature. Comparison of the performance of all the strategies validates the superiority of the proposed strategy and shows that the FTC based on proposed adaptive MLNN strategy provides better robustness to various situations such as disturbances and uncertainties. It is concluded that the proposed strategy can be integrated into the aircraft for the purpose of fault diagnosis, fault isolation and FTC scheme for increasing the performance of the system.

The induction motor drive is simple in construction, rugged, safe, low-maintenance, and are variable speed motor drive but the cost has increased while making variable speed drive with use of modern control schemes. Therefore, researchers are discovering ways to reduce the cost while achieving variable speed control. One way is by getting rid of speed sensor in the motor shaft. It can reduce program complexity and improve reliability while minimizing the cost. The recent trend in the sensorless control of induction motor drive is to achieve successful reference tracking of estimated speed at low or zero speed. The vector control due to decoupled control of stator flux and rotor torque in induction motor is widely applied for speed control. In this paper, a sensorless vector control of induction motor with fuzzy-based rotor-flux MRAS topology is proposed. The fuzzy logic controller in the speed estimator block has achieved tremendous improvement in the speed estimation at low and even zero speed proving it to be superior to other sensorless control methods. The controller parameter calculation methods are also presented. The model is simulated in MATLAB/SIMULINK software. The results showed satisfactory improvement in the system performance especially at low or even zero speed.

This paper displays a unique adaptable Neuro-Fuzzy Controller (NFC)-based speed control for three-phase induction motor drive. The suggested NFC integrates fuzzy logic idea with a four-layer Artificial Neural Network (ANN). Speed and change in speed are sent as input to Neuro-Fuzzy Controller and it winds up noticeably fit for real-time electromechanical drives. The complete simulation model for indirect vector control of induction motor including the suggested NFC is developed. Induction motor assumes an imperative part in the field of electric drives. Without genuine controlling of the speed, it is difficult to accomplish required errand for specific application. AC motors are solid, less cost, reliable, and maintenance free. In light of absence of capacity of regular control strategies like PID and PI controllers to work in a broad range of operations, AI-based controllers are extensively utilized as a part of the industry like Neural Networks, Fuzzy Logic, and Neuro-Fuzzy controller. The principle issue with the typical fuzzy-based controllers is that the parameters related with the membership functions and the rules depend predominantly on instinct of the specialists, fuzzy logic cannot naturally get the rules utilized for settling on the decision, however, great at clarifying the decision. To overcome from this issue, Neuro-Fuzzy Controller [ability to learn without anyone else alongside decision-making] is recommended. Keeping in mind the end goal to prove the predominance of the proposed Neuro-Fuzzy Controller, the results of the suggested NFC technique is compared with the results of PI controller. NFC-based control of induction motor will end up being more trustworthy than other conventional control techniques.

Control of high performance induction motors: theory and practice

<p>This paper directed the speed-sensorless vector control of induction motor drive with PI and fuzzy controllers. Natural observer with fourth order state space model is employed to estimate the speed and rotor fluxes of the induction motor. The formation of the natural observer is similar to and as well as its attribute is identical to the induction motor. Load torque adaptation is provided to estimate the torque and rotor speed is estimated from the load torque, rotor fluxes and stator currents. There is no direct feedback in natural observer and also observer gain matrix is absent. Both the induction motor and the observer are characterized by state space model. Simple fuzzy logic controller and conventional PI controllers are used to control the speed of the induction motor in closed loop. MATLAB simulations are made with PI and fuzzy controllers and the performance of fuzzy controller is better than PI controller in view of torque ripples. The simulation results are obtained for various running conditions to exhibit the suitability of this method for sensorless vector control. Experimental results are provided for natual observer based sensorless vector control with conventional PI controller.</p>

This paper analyses the detuning effects of machine electrical parameters on the performance of unified direct flux vector control (UDFVC) of induction motor drives. Drive self-commissioning is discussed as a way to estimate parameters for better control performance and accurate torque estimation. The potential of the unification of direct flux and current vector control has been recognized for both synchronous and asynchronous AC motor drives in the literature. This control operates in (d <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> , q <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> ) stator flux coordinates with the stator flux being directly controlled by the d <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> axis voltage vector component. Machine torque is controlled using a current controller in q <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> -axis. Results for the effects of parameter mismatch on control performance are given. In this work, the detuning problem is overcome by drive self-commissioning which estimates machine parameters at start up through special tests at standstill.

A fault tolerant control (FTC) scheme for tracking control is proposed for nonlinear uncertain systems affected by actuator faults and matched uncertainties with unknown upper bound. The proposed controller utilizes backstepping control which is integrated with integral sliding mode control method. For designing the integral sliding mode controller, an adaptive law is used to estimate the unknown upper bounds of faults and uncertainties. The proposed FTC ensures satisfactory transient and steady state performances with a chattering free control input. Asymptotic stability in presence of matched uncertainties and partial loss of actuator effectiveness is guaranteed in the proposed control system. The efficiency of the proposed fault tolerant control scheme is demonstrated by simulation results.

In this Faults or process failures may drastically change system behaviour leading to performance degradation and instability. The reliability and fault-tolerance of a control system can be achieved through the design of either an ac- tive or passive Fault Tolerant Control (FTC) scheme. This paper proposes a new approach to fault compensation for FTC using fault estimation by which the faults acting in a dynamical system are estimated and compensated within an adaptive control scheme with required stability and performance robustness. The FTC scheme has an augmented state observer (ASO) in the control system, which has an intrinsic robustness in terms of the stability and performance of the estimation error. The design concepts are illustrated using the notion that the friction forces in a mechanical system can be estimated and compensated to give good control performance and stability. The example given is that of a non-linear inverted pen- dulum with Stribeck friction.