Petros Karamanakos

Direct Voltage Control of DC–DC Boost Converters Using Enumeration-Based Model Predictive Control

This paper presents a model predictive control (MPC) approach for dc-dc boost converters. A discrete-time switched nonlinear (hybrid) model of the converter is derived, which captures both the continuous and the discontinuous conduction mode. The controller synthesis is achieved by formulating an objective function that is to be minimized subject to the model dynamics. The proposed MPC strategy, utilized as a voltage-mode controller, achieves regulation of the output voltage to its reference, without requiring a subsequent current control loop. Furthermore, a state estimation scheme is implemented that addresses load uncertainties and model mismatches. Simulation and experimental results are provided to demonstrate the merits of the proposed control methodology, which include a fast transient response and a high degree of robustness.

Model Predictive Pulse Pattern Control for the Five-Level Active Neutral-Point-Clamped Inverter

In this paper, the recently introduced model predictive pulse pattern control (MP3C) strategy is adapted to the ACS 2000 medium-voltage (MV) drive of ABB. The drive system consists of a five-level active neutral-point-clamped (ANPC-5L) rectifier, an inverter, and an induction machine (IM). The inverter is fed with offline-computed optimized pulse patterns (OPPs) that produce minimum harmonic distortion in the stator windings of the ac machine. An optimal stator flux trajectory is calculated from these OPPs, and a trajectory controller tracks it in real time. In the proposed approach, trajectory tracking is based on model predictive control: a constrained optimal control problem is formulated and solved in real time in a computationally efficient manner. An event-based prediction horizon is employed in order to ensure fast tracking of the stator flux trajectory. The advantages of the proposed method are optimal steady-state behavior in terms of harmonic distortion and fast torque response. The method was tested on an MV ANPC-5L inverter coupled to a general-purpose 1.21-MW IM. Experimental results were obtained from this industrial setup, and they are presented in this paper to demonstrate the high performance of MP3C.

Model predictive control of the internal voltages of a five-level active neutral point clamped converter

In this paper, model predictive control (MPC) is introduced to control the internal voltages of an active neutral-point clamped five-level converter (ANPC-5L). The proposed control scheme aims to keep the neutral point and phase capacitors voltages of the converter within given hysteresis bounds while at the same time minimizing the switching frequency. An additional benefit of the controlled voltages is a reduced level of output current distortion. The large number of redundant states that exist in multi-level converters makes it possible for all the objectives to be achieved. A short horizon is employed in order to ensure a manageable level of complexity. At the same time extrapolation is used to bring the performance to the desired level. Simulation results that substantiate the effectiveness of the proposed approach are presented.

Model predictive pulse pattern control for the five-level active neutral point clamped inverter

In this paper, the recently introduced control strategy referred to as model predictive pulse pattern control (MP3C) is adapted to the ACS 2000 five-level power converter of ABB. The drive consists of an induction machine and a five-level active neutral-point clamped (ANPC-5L) inverter. The power inverter is fed with optimized pulse patterns (OPPs) that produce minimum harmonic distortion in the stator winding of the ac machine. An optimal stator flux trajectory is calculated from these OPPs and a trajectory controller tracks it in real-time. In the proposed approach, trajectory tracking is based on model predictive control (MPC): a constrained optimal control problem is formulated and solved in real-time in a time-efficient manner. An event-based prediction horizon is employed in order to ensure fast tracking of the stator flux trajectory. The advantages of the proposed method are optimal steady-state behavior in terms of harmonic distortion and fast torque response. The method was tested on a pilot ACS 2000 power converter coupled to a general-purpose 1.21-MW induction machine. Experimental results were obtained from this industrial setup; they are presented in this paper to demonstrate the high performance of MP3C.

Direct voltage control of DC-DC boost converters using model predictive control based on enumeration

This paper presents a model predictive control (MPC) approach for the dc-dc boost converter. Based on a hybrid model of the converter suitable for both continuous and discontinuous conduction mode an objective function is formulated, which is to be minimized. The proposed MPC scheme, utilized as a voltage-mode controller, achieves regulation of the output voltage to its reference, without requiring a subsequent current control loop. Simulation and experimental results are provided to demonstrate the merits of the proposed control methodology, which include fast transient response and robustness.

Direct model predictive current control of DC-DC boost converters

For dc-dc boost converters, this paper presents a model predictive control (MPC) algorithm, which directly manipulates the switch, thus not requiring a modulator. The proposed control scheme is implemented as a current-mode controller, implying that two control loops are employed, with the inner loop being designed in the framework of MPC. Two different objective functions to be minimized are formulated and investigated. As a prediction model, a hybrid model of the converter is used, which captures both the continuous and the discontinuous conduction mode. The proposed control strategy achieves very fast current regulation, while exhibiting a modest computational complexity. Simulation and experimental results substantiate the effectiveness of the proposed approach.

Variable switching point predictive torque control

In this paper an approach to include a variable switching time point into predictive torque control (PTC) is introduced. In PTC the switching frequency is limited by the sampling frequency; its theoretical maximum value is half the sampling frequency. In reality, however, the switching frequency is lower than this value, resulting in high current and torque ripples compared to modulator-based control methods. In order to overcome this an optimization problem is formulated and solved in real-time. The goal is to find the time point at which the switches of the inverter should change state in order to not only achieve the regulation of the torque and the flux magnitude to their references, but also the minimization of the torque ripple. Further advantages of the proposed method include the design flexibility and great performance during transients. Experimental results that verify the performance of the presented control strategy are included.

Predicting insomnia in medical wards: the effect of anxiety, depression and admission diagnosis

OBJECTIVEnInsomnia is frequently underrecognized in medical wards; therefore, we assessed the prevalence and explored medical and psychological variables associated with insomnia.nnnMETHODnThe Athens Insomnia Scale and the Hospital Anxiety and Depression Scale (HADS) were completed in 235 inpatients along with demographic data, admission diagnosis, lifetime psychiatric diagnosis and prescribed psychotropics.nnnRESULTSnThe overall insomnia prevalence was 37%. Logistic regression showed that HADS anxiety and depression cases and patients with infections were more likely to have insomnia (OR 24.2, 6.1 and 5.4, respectively).nnnCONCLUSIONSnPatients with depressive and mainly anxiety symptoms are more likely to experience insomnia in medical wards. Patients with infections are also likely to have insomnia, independently of depressive and anxiety symptoms, and appropriate interventions should be applied.

Model predictive control of the interleaved DC-DC boost converter with coupled inductors

This paper proposes a model predictive control (MPC) scheme for the interleaved dc-dc boost converter with coupled inductors. The main control objectives are the regulation of the output voltage to its reference value, despite changes in the input voltage and the load, and the equal sharing of the load current by the two circuit inductors. An inner control loop, using MPC, regulates the input current to its reference that is provided by the outer loop, which is based on a load observer. Simulation results are provided to highlight the performance of the proposed control scheme.

Heuristic variable switching point predictive current control for the three-level neutral point clamped inverter

This paper presents a variable switching point predictive current control (VSP2CC) method for induction machines (IMs) driven by a three-level neutral point clamped (NPC) inverter with a heuristic preselection of the optimal voltage vector. Enumeration-based model predictive control (MPC) methods are very simple, easy to understand and, in general, offer the possibility to control any nonlinear system with arbitrary user-defined terms in the cost function. However, the two most important drawbacks are the increased computational effort which is required and the high ripples on the controlled variables which limit the applicability of these methods. These high ripples result from the fact that in enumeration-based MPC algorithms the actuating variable can only be changed at the beginning of a sampling interval. However, by changing the applied voltage vector within the sampling interval, a voltage vector can be applied for a shorter time than one sample, which results in a reduced ripple. Since this strategy leads to an additional overhead which is crucial especially for multilevel inverters, it is combined with a heuristic preselection of the optimal voltage vector to reduce the calculation effort. Experimental results are provided to verify the proposed strategy. Furthermore, it will be shown experimentally that a conventional enumeration-based MPC method will lead to very low switching frequencies and high current ripples at low machine speeds; this significant drawback can be overcome with the proposed VSP2CC strategy.