An Active Fault-Tolerant Control Strategy for Current Sensors Failure for Induction Motor Drives Using a Single Observer for Currents Estimation and Axes Transformation

This paper proposes a fault-tolerant control technique against current sensors failure in direct torque controlled induction motors drives, based on a new modification of Luenberger observer for currents estimation and axes transformation for vector rotation. Several important aspects are covered in the proposed algorithm, such as the detection of sensors failure, the isolation of faulty sensors, and the reconfiguration of the control system by a correct estimation. A logic circuit ensures fault detection by analyzing the residual signal between the measured and estimated quantities, while a single observer performs the task of estimating the line currents. In addition, a decision logic circuit isolates the erroneous signal and simultaneously selects the appropriate estimated current signal. An axes transformation ensures rotation from (a,b) to (α,β), which keeps a low-cost control using only two current sensors. The proposed scheme is tested on MATLAB/Simulink environment and experimentally validated in a laboratory prototype mainly containing a dS1104 card and 4 kW induction motor.

Application of Multilayer Observer for a Drive System with Flexibility

This paper proposes a new estimation algorithm based on the Luenberger observer methodology and multilayer concept. The proposed multi-layer Luenberger observer (MLO) is implemented in the control structure designated for a two-mass system. Two types of aggregation mechanism are evaluated in the paper. The MLO ensures better estimation quality of the mechanical state variables: motor speed, shaft torque, load speed and load torque, as compared to the classical single observer. The more accurate estimated states, the more precise closed-loop control is guaranteed. MLO is designated for the system where initial conditions of the plant are not known or the state variables can change rapidly (load torque in the considered case). The estimation algorithm and control strategy is evaluated through simulation and experimental tests. The obtained results confirm efficiency of the proposed MLO.

Design of a soft sensing technique for measuring pitch and yaw angular positions for a Twin Rotor MIMO System

Background: This paper presents a soft sensor design technique for the estimation of pitch and yaw angular positions of a Twin Rotor MIMO System (TRMS). The objective of the proposed work was to calculate the value of pitch and yaw angular positions using a stochastic estimation technique. Methods: Measurements from optical sensors were used to measure fan blade rotations per minute (RPM). The Kalman filter, which is a stochastic estimator, was used in the proposed system and its results were compared with those of the Luenberger observer and neural network. The Twin Rotor MIMO System is a nonlinear system with significant cross-coupling between its rotors. Results: The estimators were designed for the decoupled system and were applied in real life to the coupled TRMS. The convergence of estimation to the actual values was checked on a practical setup. The Kalman filter estimators were evaluated for various inputs and disturbances, and the results were corroborated in real-time. Conclusion: From the proposed work it was seen that the Kalman filter had at least Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time Absolute Error (ITAE) as compared to the neural network and the Luenberger based observer.

Time-Delay Luenberger Observer Design for Sliding Mode Control of Nonlinear Markovian Jump Systems via Event-Triggered Mechanism

This paper is focused on the stabilization of Takagi–Sugeno fuzzy model-based Markovian jump systems with the aid of a delayed state observer. Due to network-induced constraints in the communication channel, a delay partition method combined with an event-triggered mechanism is proposed to design the observer. Then, a novel integral sliding surface is designed, based on which sliding mode dynamics is obtained. Further, according to stochastic stability theory, feasible conditions are provided to ensure the sliding mode dynamics and the error dynamics have an H∞ attenuate level γ. The challenge is to deal with the issue that transition rates may be totally unknown. Moreover, an observer-based sliding mode controller is constructed to ensure the finite-time reachability of the predefined sliding surface. Finally, a numerical example based on a robotic manipulator is given to verify the effectiveness of the proposed method.

Prediction, Control and Energy Analyses of Hydraulic Transformer Based Heave Compensator

Heave compensators are widely used in offshore equipments to decouple the load motion from the wave induced ship motion. Hydraulic transformer based heave compensator (HTHC) can better compensate the ship’s heave in comparison with passive heave compensators (PHC) under changing sea conditions, meanwhile the accumulators’ volume is decreased significantly. Here in this paper, some further discussions about HTHC are given on the aspects of prediction, controller design and energy saving through simulation. Results turn out that heave prediction based on sliding mode observer is better than the Luenberger observer based one; chattering can be reduced through back-stepping method. The controller is robust when the load is perturbed by uncertain forces, and energy consumption of HTHC is about 56% of the one in an equal-sized hybrid active heave compensator (HAHC) meanwhile its total installed power can be reduced by 70%.

Self-Correcting Virtual Current Sensor Based on the Modified Luenberger Observer for Fault-Tolerant Induction Motor Drive

Fault-tolerant control (FTC) solutions are increasingly being used in modern drive systems with AC motors. Such systems provide a higher degree of security and solutions that allow the on-line detection and localization of failures, as well as the switching of the control mode to a mode that allows us to continue the operation or safely stop the drive system. As the current sensors (CSs) are necessary to ensure precise control of the AC motors, in the event of their failure, one of two strategies can be used—hardware or software redundancy. The first strategy requires the use of additional measuring sensors. For this reason, the algorithmic solution, based on the Luenberger Observer (LO), has been proposed in this article as one of the software redundancy methods. In contrast to methods presented in the literature, the proposed solution allows one not only to compensate the stator current in a phase with a faulty CS, but also to adjust the correction of current estimation based on a measured signal in the other phase with a healthy CS. Extensive simulation studies in the direct rotor flux-oriented control (DRFOC) structure with the induction motor (IM) confirm the effectiveness of the proposed method. In addition, the proposed solution allows the drive system to be controlled even if all CSs are damaged.

An Inductor Current Sensorless Control Strategy Based on Modified VSG Method for Single-Phase Microgrid Application With Seamless Transfer Capability

This paper proposes an inductor current sensorless control strategy based on modified virtual synchronous generator (VSG) method for single-phase inverter-interfaced microgrid application. Firstly, the outer power loop with Q-U integral term is presented for output reactive power enhancement, and an inner voltage regulation loop based on luenberger state observer is proposed to reduce the inductor current sensor. Meanwhile, in order to improve the response speed of the observer, the luenberger observer is designed based on the optimal pole assignment method. Secondly, a seamless switching strategy based on the modified VSG method is proposed, which can realize the seamless transition between the island mode and grid-connected mode. Finally, a single-phase 3kW VSG prototype is built, and the effectiveness and correctness of the proposed control strategy is verified by the simulation and experimental results.

Dynamic Modelling and Model Predictive Control of a Continuous Pulp Digester

This work explores the model predictive controller design of the continuous pulp digester process consisting of the co-current zone and counter-current zone modelled by a set of nonlinear coupled hyperbolic partial differential equations (PDE). The distributed parameter system of interest is not spectral and slow-fast dynamic separation does not hold. To address this challenge, the nonlinear continuous-time model is linearized and discretized in time utilizing the Cayley-Tustin discretization framework, which ensures system theoretic properties and structure preservation without spatial discretization or model reduction. The discrete model is used in the full state model predictive controller design, which is augmented by the Luenberger observer design to achieve the output constrained regulation. Finally, a numerical example is provided to demonstrate the feasibility and applicability of the proposed controller designs.