A short predictive Model Predictive Control (MPC) approach for hybrid characteristics analysis in DC-DC converter

Historically, the MPC has been successfully applied in drives system for over a decade. Furthermore, the DC-DC converter naturally deals with high switching phenomenon that contributes to the challenging in control approach. Its operation conventionally associated with PI/PID controller in order to meet the desired output. However, the PI/PID controller lacking in getting a good transient response since this controller highly depends on the controller gains. Recently, an advanced controller has been proposed in the literature for the purpose to enhance the DC-DC converter performance. Hence, in this thesis, the short prediction horizon of MPC using search tree optimization that generates low switching states phenomenon is proposed. The MPC algorithm is developed based on the hybrid characteristic signals from the DC-DC converter. The load changes due to the increasing or decreasing the loads (could be happened of heating effect) will affect the tracking of the output voltage. The Kalman Filter (KF) is used for load estimation for smoothing and tracking the output voltage. The performance of short prediction horizons is being compared to PI controller in terms of transient response during the start-up scenario. The results show that the proposed controller has a better response than PI controller, which is the overshoot has been reduced to more than 50% and the settling time more faster about 25% than PI controller during start-up scenario. Therefore, this control approach for DC-DC buck converter has produced the promising output transient performance when compared with the conventional PI controller while also minimizing the switching sequence phenomenon

Optimized active disturbance rejection control for DC-DC buck converters with uncertainties using a reduced-order GPI observer

The output voltage regulation problem of a PWM- based DC-DC buck converter under various sources of uncertainties and disturbances is investigated in this paper via an optimized active disturbance rejection control (ADRC) approach. Aiming to practical implementation, a new reduced-order generalized proportional integral (GPI) observer is first designed to estimate the lumped (possibly time-varying) disturbances within the DC- DC circuit. By integrating the disturbance estimation information raised by the reduced-order GPI observer (GPIO) into the output prediction, an optimized ADRC method is developed to achieve optimized tracking performance even in the presence of distur- bances and uncertainties. It is shown that the proposed controller will guarantee the rigorous stability of closed-loop system, for any bounded uncertainties of the circuit, by appropriately choosing the observer gains and the bandwidthfactor. Experimental results illustrate that the proposed control solution is characterised by improved robustness performance against various disturbances and uncertainties compared to traditional ADRC and integral MPC approaches

H∞ based control of a DC/DC buck converter feeding a constant power load in uncertain DC microgrid system

DC microgrids are gaining more and more popularity and are becoming a more viable alternative to AC microgrids (MGs) due to their advantages in terms of simpler power converter stages, flexible control algorithms and the absence of synchronization and reactive power. However, DC-MGs are prone to instability issues associated with the presence of nonlinear loads such as constant power loads (CPL) known by their incremental negative impedance (INI), which may lead to voltage collapse of the main DC Bus. In this paper, -based controller of a source side buck converter is designed to avoid the instability issues caused by the load-side converter acting as a CPL. Besides, the proposed controller allows a perfect rejection of all perturbations that may arise from parameter variations, input voltage and CPL current fluctuations. The design process of H-based controller is based on the Golver Doyle Optimization Algorithm (GDOA), which requires an augmented system extracted from the small-signal model of the DC/DC converter including the mathematical model of parameter variations and overall external perturbations. The​ based controller involves the use of weight functions in order to get the desired performances. The proposed controller is easy to implement and lead to reducing the implementation cost and avoid the use of current measurement that may have some disadvantages. The derived controller is validated by simulation performed in Psim software and experimental setup

Improvement of the linear quadratic regulator control applied to a DC-DC boost converter driving a permanent magnet direct current motor

This article discusses a new robust control technique that enables the DC-DC boost converter driving a permanent magnet direct current (PMDC) motor to operate in high static and dynamic performances. The new technique is based on the design of a both linear quadratic regulator (LQR) and linear quadratic regulator-proportional integral (LQR-PI) type controllers, which have the advantage of eliminating oscillations, overshoots and fluctuations on different characteristics in steady-state system operation. In order to increase the output voltage, the LQR regulator is combined with a first-order system represented in the form of a closed-loop transfer function, the latter raising the output voltage to 24 volts, this voltage is enough to drive the permanent magnet direct current motor. The contribution of this paper is the creation of a robust control system represented in the form of a hybrid corrector able to regulate steady-state and transient disturbances and oscillations as well as to increase DC-DC boost converter output voltage for the PMDC motor to operate at rated voltage. The results of the three control techniques are validated by MATLAB Simulink

Adaptive Optimal Control of Faulty Nonlinear DC Microgrids with Constant Power Loads: Dual-Extended Kalman Filter Approach

This article investigates the problem of estimating actuator fault and states and controlling the bus voltage in direct current microgrids (DC MGs) with linear and nonlinear constant power loads (CPLs). It is considered that the DC MG states are not fully measurable and the utilized sensors are not ideal and noisy. Additionally, the actuator fault occurs and it is modeled as an additive term in the power system dynamics. These issues, including nonlinearities, un-measurable states, noisy measures, and actuator fault indispensably degrade the operation of the DC MG. To solve this issue, initially, a dual-extended Kalman filter (dual-EKF) is suggested for the fault and state estimation. It decomposes the process of estimating the state and actuator fault to reduce the online computational burden. For the control purpose, a linear parameter varying (LPV) model predictive control (MPC) is suggested to regulate the current and voltage of the DC MG. It benefits the nonlinear system modeling of LPV representation and constrained-based design procedure of the MPC to result in an accurate and low online computational burden dealing with system constraints. By deploying the overall robust adaptive dual-EKF estimation-based LPV-MPC, there is no need to have any prior knowledge of all system states and actuator faults in prior. The theoretical analysis and controller design are validated by numerical simulations on a typical islanded DC MG and comparisons are done with state-of-the-art estimation and control strategies.©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Design and Implementation of Takagi-Sugeno Fuzzy Tracking Control for a DC-DC Buck Converter

This paper presents the design and implementation of a Takagi-Sugeno (T-S) fuzzy controller for a DC-DC buck converter using Arduino board. The proposed fuzzy controller is able to pilot the states of the buck converter to track a reference model. The T-S fuzzy model is employed, firstly, to represent exactly the dynamics of the nonlinear buck converter system, and then the considered controller is designed on the basis of a concept called Virtual Desired Variables (VDVs). In this case, a two-stage design procedure is developed: i) determine the reference model according to the desired output voltage, ii) determine the fuzzy controller gains by solving a set of Linear Matrix Inequalities (LMIs). A digital implementation of the proposed T-S fuzzy controller is carried out using the ATmega328P-based Microcontroller of the Arduino Uno board. Simulations and experimental results demonstrate the validity and effectiveness of the proposed control scheme

Design and Advanced Model Predictive Control of Wide Bandgap Based Power Converters

The field of power electronics (PE) is experiencing a revolution by harnessing the superior technical characteristics of wide-band gap (WBG) materials, namely Silicone Carbide (SiC) and Gallium Nitride (GaN). Semiconductor devices devised using WBG materials enable high temperature operation at reduced footprint, offer higher blocking voltages, and operate at much higher switching frequencies compared to conventional Silicon (Si) based counterpart. These characteristics are highly desirable as they allow converter designs for challenging applications such as more-electric-aircraft (MEA), electric vehicle (EV) power train, and the like. This dissertation presents designs of a WBG based power converters for a 1 MW, 1 MHz ultra-fast offboard EV charger, and 250 kW integrated modular motor drive (IMMD) for a MEA application. The goal of these designs is to demonstrate the superior power density and efficiency that are achievable by leveraging the power of SiC and GaN semiconductors. Ultra-fast EV charging is expected to alleviate the challenge of range anxiety , which is currently hindering the mass adoption of EVs in automotive market. The power converter design presented in the dissertation utilizes SiC MOSFETs embedded in a topology that is a modification of the conventional three-level (3L) active neutral-point clamped (ANPC) converter. A novel phase-shifted modulation scheme presented alongside the design allows converter operation at switching frequency of 1 MHz, thereby miniaturizing the grid-side filter to enhance the power density. IMMDs combine the power electronic drive and the electric machine into a single unit, and thus is an efficient solution to realize the electrification of aircraft. The IMMD design presented in the dissertation uses GaN devices embedded in a stacked modular full-bridge converter topology to individually drive each of the motor coils. Various issues and solutions, pertaining to paralleling of GaN devices to meet the high current requirements are also addressed in the thesis. Experimental prototypes of the SiC ultra-fast EV charger and GaN IMMD were built, and the results confirm the efficacy of the proposed designs. Model predictive control (MPC) is a nonlinear control technique that has been widely investigated for various power electronic applications in the past decade. MPC exploits the discrete nature of power converters to make control decisions using a cost function. The controller offers various advantages over, e.g., linear PI controllers in terms of fast dynamic response, identical performance at a reduced switching frequency, and ease of applicability to MIMO applications. This dissertation also investigates MPC for key power electronic applications, such as, grid-tied VSC with an LCL filter and multilevel VSI with an LC filter. By implementing high performance MPC controllers on WBG based power converters, it is possible to formulate designs capable of fast dynamic tracking, high power operation at reduced THD, and increased power density

High-performance motor drives

This article reviews the present state and trends in the development of key parts of controlled induction motor drive systems: converter topologies, modulation methods, as well as control and estimation techniques. Two- and multilevel voltage-source converters, current-source converters, and direct converters are described. The main part of all the produced electric energy is used to feed electric motors, and the conversion of electrical power into mechanical power involves motors ranges from less than 1 W up to several dozen megawatts

Comparison of single-phase matrix converter and H-bridge converter for radio frequency induction heating

This paper compares the newly developed single-phase matrix converter and the more conventional H- bridge converter for radio frequency induction heating. Both the converters exhibit unity power factor, very low total harmonic distortion at the utility supply interface, good controllability under soft switching condition for a wide range of power, and high efficiencies, whilst still having simple structures. A novel switching control pattern has been proposed for the matrix converter in order to maintain the comparable performance to the H-bridge converter. Simulation and experimental results for both converters are presented. Comparisons between two converters have confirmed the excellent performance of the proposed matrix converter