Kalman Filtering Applied to Induction Motor State Estimation

This chapter presents a full definition and explanation of Kalman filtering theory, precisely the filter stochastic algorithm. After the definition, a concrete example of application is explained. The simulated example concerns an extended Kalman filter applied to machine state and speed estimation. A full observation of an induction motor state variables and mechanical speed will be presented and discussed in details. A comparison between extended Kalman filtering and adaptive Luenberger state observation will be highlighted and discussed in detail with many figures. In conclusion, the chapter is ended by listing the Kalman filtering main advantages and recent advances in the scientific literature

Induction Motor Performance Improvement using Super Twisting SMC and Twelve Sector DTC

Induction motor (IM) direct torque control (DTC) is prone to a number of weaknesses, including uncertainty, external disturbances, and non-linear dynamics. Hysteresis controllers are used in the inner loops of this control method, whereas traditional proportional-integral (PI) controllers are used in the outer loop. A high-performance torque and speed system is consequently needed to assure a stable and reliable command that can tolerate such unsettled effects. This paper treats the design of a robust sensorless twelve-sector DTC of a three-phase IM. The speed controller is conceived based on high-order super-twisting sliding mode control with integral action (iSTSMC). The goal is to decrease the flux, torque, the current ripples that constitute the major conventional DTC drawbacks. The phase current ripples have been effectively reduced from 76.92% to 45.30% with a difference of 31.62%. A robust adaptive flux and speed observer-based fuzzy logic mechanism are inserted to get rid of the mechanical sensor. Satisfactory results have been got through simulations in MATLAB/Simulink under load disturbance. In comparison to a conventional six-sector DTC, the suggested technique has a higher performance and lower distortion rate

Power Quality Improvement using a New DPC Switching Table for a Three-Phase SAPF

This research focuses on the analysis and design of robust direct power control (DPC) for a shunt active power filter (SAPF). The study proposes a novel switching table design based on an analysis of the impact of inverter switching vectors on the derivatives of instantaneous reactive and active powers. The goal is to reduce the number of commutations by eliminating null vectors while maintaining the desired DC-bus voltage using a PI regulator-based anti windup technique. Additionally, a robust PLL structure-based band pass multivariate filter (BPMVF) is utilized to enhance the network voltage. The research demonstrates the effectiveness of the suggested power control through extensive simulation results, showing high performance in both transient and steady-state conditions. The proposed approach offers the advantages of sinusoidal network current, and unitary power factor, and eliminates the need for current regulators and coordinate transformations or PWM generators. Further research directions could explore the practical implementation and real-world performance of this technique in power systems

Robust Voltage Vector-Controlled Three-Phase SAPF-based BPMVF and SVM for Power Quality Improvement

The multiplication of nonlinear loads leads to significant degradation of the energy quality, thus the interconnection network is subject to being polluted by the generation of harmonic components and reactive power, which causes a weakening efficiency, especially for the power factor. In three-phase systems, they can cause imbalances by causing excessive currents at the neutral. This research treats the operation of robust voltage-oriented control (VOC) for a shunt active power filter (SAPF). The main benefit of this technique is to guarantee a decoupled control of the active and reactive input currents, as well as the input reference voltage. To sustain the DC voltage, a robust PI-structure-based antiwindup is inserted to ensure active power control. Besides, a robust phase-locked loop (PLL)-based bandpass multivariable filter (BPMVF) is used to improve the network voltage quality. Furthermore, a space vector modulation (SVM) is designed to replace the conventional one. A sinusoidal network current and unitary power factor are achieved with fewer harmonics. The harmonics have been reduced from 27.98% to 1.55% which respects the IEEE 519-1992 standard. Expanded simulation results obtained from the transient and steady-state have demonstrated the high performance of the suggested control scheme

Synchronous Reluctance Motor Performance Improvement Using MTPA Control Strategy and Five-Level Inverter Topology

An improved vector control method is presented in this study to enhance synchronous reluctance motor (SynRM) performance. The maximum torque per ampere (MTPA) technique has demonstrated good dynamic properties since the torque control is closely tied to the current control. The selection of the control approach is primarily influenced by how the reference current values will be defined. Additionally, a five-level neutral-point-clamped (NPC) inverter replaces the traditional two-level inverter. Only eight voltage vectors can be produced by a two-level inverter, whereas one hundred twenty-five voltage vectors can be generated by a five-level inverter. The goal is to produce an output voltage vector that closely resembles the reference voltage vector in order to ensure a quick response on the one hand and enhance dynamic performance on the other. An exact comparison of the suggested vector control strategy's properties is made once it has been simulated in MATLAB/Simulink. The acquired findings are satisfactory and high performance is attained in terms of response time, torque ripple reduction, and current waveform improvement

A Comparative Study of Nonlinear Control Schemes for Induction Motor Operation Improvement

In the objective of improving the performance of induction motor operation and ensuring a robust control against different uncertainties and external disturbances, especially at low-speed regions, this research highlights the main features of two nonlinear control techniques. First, the control design is based on the backstepping approach (BSA) with integral action, and then the sliding mode control (SMC) theory. The BSA principle is to define successive causal relations in order to construct the control law in a recursive and systematic way. This allows overcoming the obstacle of the higher-order system's dimension. SMC is designed to drive and then constrain the system state to lie within a neighborhood of the switching surface, this provides very strong and inherent robustness to the resulting controllers. The main reason behind developing the nonlinear control techniques is to ensure a decoupled control of the machine. Besides, it guarantees the stability of the overall system by tracking the speed reference with the fewest static error. Moreover, as the sensorless control increases the reliability and decreases the cost of the control system, an extended Kalman filter is implemented to improve speed and flux observation. The simulations of all the discussed results have been obtained by MATLAB/Simulink

Induction Motor DTC Performance Improvement by Inserting Fuzzy Logic Controllers and Twelve-Sector Neural Network Switching Table

Human civilization has changed forever since induction motors were invented. Induction motors are widely used and have become the most prevalent electrical componentsdue to their beneficial characteristics. Many control strategies have been developed for their performance improvement, starting from scalar to vector to direct torque control. The latter, which is a class of vector control, was proposed as an alternative to ensure separate flux and torque control while remaining completely in a stationary reference frame. This technique allows direct inverter switching and reasonable simplicity compared to other vector control techniques, and it is less sensitive to parameter variation. Yet, the use of hysteresis controllers in conventional DTC involves undesired ripples in the stator current, flux, and torque, which lead to bad performances. This paper aims to minimize the ripple level and ensure the system’s performance in terms of robustness and stability. To generate the appropriate reference control voltages, the proposed method is an improved version of DTC, which combines the power of fuzzy logic, neural networks, and an increased number of sectors. Satisfactory results were obtained by numerical simulation in MATLAB/Simulink. The proposed method was proven to be a fast dynamic decoupled control that robustly responds to external disturbance and system uncertainties

Induction Motor DTC Performance Improvement by Inserting Fuzzy Logic Controllers and Twelve-Sector Neural Network Switching Table

Human civilization has changed forever since induction motors were invented. Induction motors are widely used and have become the most prevalent electrical componentsdue to their beneficial characteristics. Many control strategies have been developed for their performance improvement, starting from scalar to vector to direct torque control. The latter, which is a class of vector control, was proposed as an alternative to ensure separate flux and torque control while remaining completely in a stationary reference frame. This technique allows direct inverter switching and reasonable simplicity compared to other vector control techniques, and it is less sensitive to parameter variation. Yet, the use of hysteresis controllers in conventional DTC involves undesired ripples in the stator current, flux, and torque, which lead to bad performances. This paper aims to minimize the ripple level and ensure the system’s performance in terms of robustness and stability. To generate the appropriate reference control voltages, the proposed method is an improved version of DTC, which combines the power of fuzzy logic, neural networks, and an increased number of sectors. Satisfactory results were obtained by numerical simulation in MATLAB/Simulink. The proposed method was proven to be a fast dynamic decoupled control that robustly responds to external disturbance and system uncertainties