Nominal Point Research Articles

Synthesis of a Robust Regulator for the Lateral Motion Parameters of an Unmanned Aerial Vehicle

The article deals with the control system for the lateral motion of an unmanned aerial vehicle with a robust regulator. We carried out the synthesis of a robust regulator on the basis of the H∞ theory for a multidimensional control object written in a vector-matrix form. It is a linear dynamical system of the sixth order. The controller is designed to implement the flight path azimuth directional method and uses the combined control of the turn of the aircraft. We discuss and analyze the accuracy, stability and speed response of the system at the nominal point and with changed model parameters. The efficiency of suppression of deterministic perturbations is also investigated.

A Probabilistic Forecast-Driven Strategy for a Risk-Aware Participation in the Capacity Firming Market

This paper addresses the energy management of a grid-connected renewable generation plant coupled with a battery energy storage device in the capacity firming market, designed to promote renewable power generation facilities in small non-interconnected grids. The core contribution is to propose a probabilistic forecast-driven strategy, modeled as a min-max-min robust optimization problem with recourse. It is solved using a Benders-dual cutting plane algorithm and a column and constraints generation algorithm in a tractable manner. A dynamic risk-averse parameters selection strategy based on the quantile forecasts distribution is proposed to improve the results. A secondary contribution is to use a recently developed deep learning model known as normalizing flows to generate quantile forecasts of renewable generation for the robust optimization problem. This technique provides a general mechanism for defining expressive probability distributions, only requiring the specification of a base distribution and a series of bijective transformations. Overall, the robust approach improves the results over a deterministic approach with nominal point forecasts by finding a trade-off between conservative and risk-seeking policies. The case study uses the photovoltaic generation monitored on-site at the University of Li\`ege (ULi\`ege), Belgium.

Hybrid Excitation PM Synchronous Motors: Part I – Per Unit Analysis

A synchronous machine is analysed, characterised by a rotor including both Permanent Magnets (PMs) and excitation winding. The PMs produce a fixed flux while the excitation winding is adopted to modulate the rotor flux. The nominal point and flux-weakening performance of such a synchronous machine is compared to that of a more commonly used PM machine, to the aim of highlighting advantages and drawbacks. For the sake of achieving a more general comparison, a per unit system is introduced. Thanks to this normalization all the combinations of the machine parameters are taken into account, for both standard PM and HEPM machine. Fixing the same performance at nominal speed, it is shown that the HEPM machine exhibits a higher capability and power factor equal to one during flux-weakening operations. The possibility to modulate the rotor flux allows to overcome the speed limit of the standard PM machines and to keep a high torque and power in a wide range of speeds.

Bubble-injection-enabled significant reduction of supercooling and controllable triggering of crystallization of erythritol for medium-temperature thermal energy storage

Erythritol, having a nominal melting point of ∼118 °C, has been considered a candidate phase change material (PCM) for medium-temperature thermal energy storage (TES) due to its large latent heat of fusion (∼330 kJ/kg). However, it suffers from severe supercooling effect, up to several tens of degrees Celsius, upon crystallization by cooling, which remains to be a critical issue for its application. Here we propose a novel method of injection of gas bubbles into subcooled liquid erythritol to facilitate the nucleation of erythritol crystals, so as to reduce its degree of supercooling. Using this method, we obtained successfully an unprecedented reduction of the degree of supercooling of erythritol down to only 5 °C, which is much lower than those achieved by other conventional methods like adding a nucleating agent or ultrasonication. As a bonus, the latent heat of crystallization was found to be greatly increased by nearly 50%, from 218.2 kJ/kg to 322.3 kJ/kg. The injection of bubbles also enables an effective way for actively triggering the crystallization of erythritol in a controllable manner. Our results showed that by changing the injecting timing of bubbles, crystallization can always be triggered immediately with only the crystallization point being varied over a wide range. The injection of bubbles is thus deemed to be a highly-efficient, cost-effective, and scalable method for addressing the supercooling issue of erythritol, and other similar PCMs with deep supercooling, making it more promising for TES applications. • We propose a new method by injection of bubbles to reduce supercooling of erythritol. • The degree of supercooling can be decreased down to only 5 °C, a record-low value. • The latent heat of crystallization of erythritol is increased by nearly 50% as a bonus. • This method also enables an effective way for controllable triggering of crystallization.

An Optimal Procedure for the Design of Discrete Constrained Lens Antennas with Minimized Optical Aberrations. Part I: Two-Dimensional Architectures

Despite to the significant literature available on the design and applications of two-dimensional constrained lens antennas, and in particular on the Rotman–Turner lens, a rigorous study focused on the minimization of optical aberrations does not seem to be available. A general procedure for the design of two-dimensional bootlace lens antennas with a flat front profile is proposed in this paper. For the 3-foci lens, the best performance is achievable when, in addition to the three nominal focal points, two additional symmetric quasi foci are present. For the 4-foci lens the best performance is obtained when the presence of one additional quasi focus on the lens axis is guaranteed. Both the 3- and 4-foci lenses, when optimized, converge to the same configuration which exhibits aberrations following a Chebyshev-like behavior and guarantees quasi 5 foci. The optimized lens architecture is such that, for every scanning angle, the aberrations in the two extreme points are the most significant and exhibit opposite values. Any variation from this optimal condition implies increased aberrations. Although a 5-foci lens with flat front profile cannot be derived, one quasi-5-foci lens is derived asymptotically starting from two completely different lens architectures. A maximization of the number of foci combined with a rigorous derivation of the focal curve turned to be the key driver to identify an optimal two-dimensional bootlace lens. The quasi 5-foci lens presented can be considered the optimum Rotman–Turner lens in terms of optical aberrations allowing to reduce the optical aberrations by about one order of magnitude as compared to the best results available in the literature.

A High Reliable SRAM-Based PUF With Enhanced Challenge-Response Space

This brief proposes a sequence-dependent SRAM-based PUF with enhanced reliability. It expands the CPRs by order of (rows <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{(sequence\,\,length\,\,}{}^{+}{}^{\,\,}{}^{2}{}^{)}\,\, \mathbf {\mathrm {\times }}$ </tex-math></inline-formula> columns) for reliable authentication. The proposed bitcell utilizes split word-lines to control two access transistors separately. The PUF mode turns on two left word-lines and two right word-lines simultaneously, including 18 transistors for generating one-bit data. This proposed technique supports rendering multiple data maps from one chip. Besides, various temperature and voltage combinations can create a reliability map for each data map. A test chip was fabricated in 40 nm CMOS technology. The measured worst bit error rate is 0.8% at the nominal point (1V, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$20 \mathbf {\mathrm {^\circ }}$ </tex-math></inline-formula> C). From a single chip, the proposed PUF achieved the hamming distances of 41.29% for one sequence with different orders and 44.93% for other sequences, respectively. The measured inter-chip hamming distance is 49.64%.

Operability thresholds for thermally damaged EBW detonators

Operability thresholds that differentiate between functional RP-87 exploding bridge wire (EBW) detonators and nonfunctional RP-87 EBW detonators (duds) were determined by measuring the time delay between initiation and early wall movement (function time). The detonators were inserted into an externally heated hollow cylinder of aluminum and fired with current flow from a charged capacitor using an exploding bridge wire (EBW initiated). Functioning detonators responded like unheated pristine detonators when the function time was 4 μs or less. The operability thresholds of the detonators were characterized with a simple decomposition cookoff model calibrated using a modified version of the Sandia Instrumented Thermal Ignition (SITI) experiment. These thresholds are based on the calculated state of the PETN when the detonators fire. The operability threshold is proportional to the positive temperature difference (ΔT) between the maximum temperature within the PETN and the onset of decomposition (∼406 K). The temperature difference alone was not sufficient to define the operability threshold. The operability threshold was also proportional to the time that the PETN had been at elevated temperatures. That is, failure was proportional to both temperature and reaction rate. The reacted gas fraction is used in the current work for the reaction correlation. Melting of PETN also had a significant effect on the operability threshold. Detonator failure occurred when the maximum temperature exceeded the nominal melting point of PETN (414 K) for 45±5 s or more.

Robust design using multiobjective optimisation and artificial neural networks with application to a heat pump radial compressor

Abstract Although robustness is an important consideration to guarantee the performance of designs under deviation, systems are often engineered by evaluating their performance exclusively at nominal conditions. Robustness is sometimes evaluated a posteriori through a sensitivity analysis, which does not guarantee optimality in terms of robustness. This article introduces an automated design framework based on multiobjective optimisation to evaluate robustness as an additional competing objective. Robustness is computed as a sampled hypervolume of imposed geometrical and operational deviations from the nominal point. In order to address the high number of additional evaluations needed to compute robustness, artificial neutral networks are used to generate fast and accurate surrogates of high-fidelity models. The identification of their hyperparameters is formulated as an optimisation problem. In the frame of a case study, the developed methodology was applied to the design of a small-scale turbocompressor. Robustness was included as an objective to be maximised alongside nominal efficiency and mass-flow range between surge and choke. An experimentally validated 1D radial turbocompressor meanline model was used to generate the training data. The optimisation results suggest a clear competition between efficiency, range and robustness, while the use of neural networks led to a speed-up by four orders of magnitude compared to the 1D code.

A compound optical path difference phase-shift solution method based on Doppler asymmetric spatial heterodyne spectral velocimetry

Asymmetric spatial heterodyne spectroscopy is a new ultra-high resolution remote sensing detection technology. Based on its features of large luminous flux, small size, and high precision, it is very suitable for high-precision detection in a deep-space environment. Because of its high sensitivity, various details may interfere with the measurement results in experiment. In this paper, from the perspective of experimental condition, considering the influences of factors such as fringe center position offset, uneven illumination, and Gaussian noise, a compound optical path difference phase-shift solution method is proposed. The simulation calculation and data analysis show that the offset of the nominal point relative to the center position will significantly affect the systematic error of spectral velocity measurement. And the compound optical path difference phase-shift solution method can smooth the environmental noise and random interference to a certain extent. For the interference fringe image with 1% Gaussian noise, the velocity measurement error can be controlled within 5‰ by using the compound optical path difference phase-shift solution method, which makes the asymmetric spatial heterodyne spectroscopy technology more suitable for space optoelectronic precision measurement.

Thermally Constrained Conceptual Deep Geological Repository Design under Spacing and Placing Uncertainties

The temperature evolution within a deep geological repository (DGR) is a key design consideration for the safe and permanent storage of the high-level radioactive waste contained inside used nuclear fuel containers (UFCs). Due to the material limitations of engineered components with respect to high temperature tolerance, the Nuclear Waste Management Organization of Canada requires the maximum temperature within a future Canadian DGR to be less than 100 °C. Densely placing UFCs within a DGR is economically ideal, but greater UFC placement density will increase the maximum temperature reached in the repository. This paper was aimed to optimize (i) the separation between UFCs, (ii) the distance between container placement rooms, and (iii) the locations of the age-dependent UFCs in the placement rooms for a conceptual DGR constructed in crystalline rock. Surrogate-based optimization reduced the amount of computationally expensive evaluations of a COMSOL Multiphysics model used to study the temperature evolution within the conceptual DGR and determined optimal repository design points. Via yield optimization, nominal design points that considered uncertainties in the design process were observed. As more information becomes available during the design process for the Canadian DGR, the methods employed in this paper can be revisited to aid in selecting a UFC placement plan and to mitigate risks that may cause repository failure.

Wind Tunnel Experiments on Interaction between Two Closely Spaced Vertical-Axis Wind Turbines in Side-by-Side Arrangement

This study aimed to determine the optimal rotor spacing of two vertical-axis wind turbines, which are simulated by miniature models arranged side-by-side with a relatively low aspect ratio. Wind tunnel experiments with a pair of 3-D printed model rotors were conducted at a uniform velocity. A series of experiments were conducted involving both incremental adjustments to the rotor gaps, g, and the rotational direction of each rotor. Increases in the power and the related flow patterns were observed in all three arrangements: Co-Rotating (CO), Counter-Up (CU), and Counter-Down (CD). The maximum phase-synchronized rotational speed occurs at the narrowest gap in the CD arrangement. Meanwhile, local maxima arise in the CO and CU arrangements at g/D &lt; 1, where D is the rotor diameter. From an engineering perspective, the optimal rotor spacing is g/D = 0.2 with the CO arrangement, using the same two rotors rotating in the same direction. Based on flow visualization using a smoke-wire method at a narrower gap opening of 0.2D, the wake width in the case of the CU arrangement was remarkably narrower than those obtained in the CO and CD arrangements. In the CU arrangement, a movement towards the center of the rotor pair of the nominal front-stagnation point of each rotor was confirmed via flow visualization. This finding explains a reduction tendency in the rotational speed of the rotors via a reduction in the lift in the CU arrangement.

Forward-looking persistent excitation in model predictive control

This work deals with the problem of integrating persistence of excitation into nonlinear constrained model predictive control to estimate uncertain parameters while guaranteeing a stable closed loop. We propose an adaptive tracking model predictive control and conditions which guarantee persistent excitation and uniformly bounded closed loop signals of nonlinear systems, despite bounded noise and parameter uncertainty. This is achieved by actively designing persistence of excitation through the computation of a reference trajectory around some nominal stationary point depending on the parameter estimate, opening up the opportunity of balancing excitation against other requirements. Appealing to the Total Stability Theorem, the results are local and solution evolves in a non-infinitesimal ball in state and estimated parameter.

Wide-range model predictive control for aero-engine transient state

To perform transient state control of an aero-engine, a structure that combines linear controller and min–max selector is widely adopted, which is inherently conservative and therefore limits the fulfillment of the engine potential. Model predictive control is a new control method that has vast application prospects in the field of aero-engine control. Therefore, this paper proposes a wide-range model predictive controller that can control the engine over a wide range within the flight envelope. This paper first introduces the engine parameters and the model prediction algorithm used by the controller. Then a wide-range model prediction controller with a three-layer nested structure is presented. These three layers of the structure are univariate controller, nominal point controller, and wide-range controller from inside to outside. Finally, by analyzing and verifying the effectiveness of the univariate controller for small-range variations and the wide-range model predictive controller for large-range parameter variations, it is demonstrated that the controller can schedule the controller’s output based on inlet altitude, Mach number, and low-pressure shaft corrected speed, and ensure that the limits are not exceeded. It is concluded that the designed wide-range model predictive controller has good dynamic effect and safety.

AS-Solar, a Tool for Predictive Maintenance of Solar Groundwater Pumping Systems

Energy for water abstraction limits the viability of some irrigable areas. Increasing efficiency and introducing renewable energy can reduce energy cost. Solar pumping is a widely recognized renewable energy solution. These pumping systems suffer special wear out due to sudden changes and for having working conditions far from the nominal points. Thus, monitoring systems are becoming more frequent for maintenance issues. A new decision support system, named AS-Solar, was developed to perform predictive maintenance. This model permits detecting if the source of the anomaly in the pump performance is the pump, the electrical components (motor, variable frequency drive (VFD) or cables) or the pumping pipe. It demands real-time data from the monitoring system and an accurate simulation model, together with an optimization process that helps in the decision making in predictive maintenance. To validate the developed model, it was applied to a complex case study of a solar pumping system of 40 kWp that abstracts groundwater from nearly 200 m deep. This pumping system has a VFD, two lines of cables up to the pump and aggressive water with slimes, which causes different problems in the pumping system. In this case study, the AS-Solar model shows an acceptable accuracy, with a relative error (RE) of the 2.9% in simulated power and 7.9% in simulated discharge.

Control design for maximal capability of disturbance rejection under general control input saturation

This paper focuses on the control problem for a basic class of nonaffine uncertain systems with general control input saturation (CIS) and piecewise constant disturbance. Instead of traditional CIS, the considered general CIS model includes the case that larger control input generates smaller control capability to capture more general engineering systems. Also, the saturation point, at which the maximum or minimum value of the saturation function of general CIS can be obtained, is assumed to be unknown. To achieve the maximal capability of disturbance rejection, this paper proposes a novel active disturbance rejection control design with online estimating both disturbance and the saturation points. Firstly, the control capability under the nominal saturation points is discussed. We demonstrate that the corresponding capability of disturbance rejection can be discussed via the domain of attraction or invariant set of the systems with general CIS despite of disturbance. Furthermore, we design an algorithm to online identify the saturation points based on the estimation of “total disturbance” obtained by extended state observer (ESO). It is proven that the maximal capability of disturbance rejection can be approached by tuning the parameters of the proposed controller. In addition, simulation results for the angular rate control of aircraft show the superiority of our control law to the traditional disturbance rejection control law.

Data-Driven Self-Optimizing Control: Unconstrained Optimization Problem

Controlled variable (CV) selection plays an important role in determining the performance of a process plant. Existing methods for CV selection through self-optimizing control requires linearization of rigorous models around nominal operating points. This is a very difficult task which results to large losses. This work presents a novel method for CV design. A necessary condition of optimality (NCO) was proposed to be the CV. The approach does not require the analytical expression of the NCO to be derived but is approximated through a single regression step based on data. Finite difference was used to approximate the NCO (gradient) using data; three finite difference schemes were employed for this purpose, which are forward, backward and central differences. Seven different cases with respect to number of sampling points, neighborhood points and finite difference schemes were investigated. To demonstrate the efficacy of the method in simplest way, it is applied to a hypothetical unconstrained optimization problem. The proposed method was found to have outperformed some existing approaches in many instances. A zero loss was recorded by some designed CVs. Central difference was found to be the best schemes among the three. Keywords— controlled variable, disturbance, finite difference, monotonicity, regression.

High energy-efficient electrical drive with multilevel inverter and widebandgap power semiconductors

Multilevel inverters are an alternative for electrical drives with DC link voltage between 560 and 750 V. In this voltage range new wide-bandgap power switches (SiC MOSFET, GaN FET) are available. The paper analyses three-, four-, five- and seven-level inverters. A simulation model of the drive system, including the 11 kW induction motor and motor filter is developed. By replacing IGBTs with SiC FETs, the twolevel inverter achieved a loss reduction of 59 % at 25 °C and 150 °C at nominal motor operation point. By using the five-level inverter with GaN FETs, a further loss reduction of 9 % only at low junction temperature is possible. With a higher number of inverter levels, the size of the motor filter can be reduced. With five inverter levels and 40 kHz switching frequency volume and weight can be reduced by 86 % and 78 % respectively. The overall efficiency of the drive system achieves 98.5 % at 25 °C and 98.1 % at 150 °C. Compared to the state of the art (two-level with IGBTs with 5 kHz), this is an improvement of 2.1 % at 25 °C and 2.7 % at 150 °C.

Shear-Induced and Nanofiber-Nucleated Crystallization of Novel Aliphatic-Aromatic Copolyesters Delineated for In Situ Generation of Biodegradable Nanocomposites.

The shear-induced and cellulose-nanofiber nucleated crystallization of two novel aliphatic–aromatic copolyesters is outlined due to its significance for the in situ generation of biodegradable nanocomposites, which require the crystallization of nanofibrous sheared inclusions at higher temperatures. The shear-induced non-isothermal crystallization of two copolyesters, namely, poly(butylene adipate-co-succinate-co-glutarate-co-terephthalate) (PBASGT) and poly(butylene adipate-co-terephthalate) (PBAT), was studied following a light depolarization technique. To have a deep insight into the process, the effects of the shear rate, shear time, shearing temperature and cooling rate on the initiation, kinetics, growth and termination of crystals were investigated. Films of 60 μm were subjected to various shear rates (100–800 s−1) for different time intervals during cooling. The effects of the shearing time and increasing the shear rate were found to be an elevated crystallization temperature, increased nucleation density, reduced growth size of lamella stacks and decreased crystallization time. Due to the boosted nucleation sites, the nuclei impinged with each other quickly and growth was hindered. The effect of the cooling rate was more significant at lower shear rates. Shearing the samples at lower temperatures, but still above the nominal melting point, further shifted the non-isothermal crystallization to higher temperatures. As a result of cellulose nanofibers’ presence, the crystallization of PBAT, analyzed by DSC, was shifted to higher temperatures.

Thermodynamic assessment of the novel concept of the energy storage system using compressed carbon dioxide, methanation and hydrogen generator

The main aim of this paper is to characterize the concept of a novel energy storage system, based on compressed CO2 storage installation, that uses an infrastructure of depleted coal mines to provide required volume of tanks, and, additionally, hydrogen generators, and a methanation installation to generate synthetic natural gas that can be used within the system or taken out of it, e.g., to a gas grid. A detailed mathematical model of the proposed solution was built using own codes and Aspen Plus software. Thermodynamic evaluation, aiming at determining parameters, composition and streams in all the most important nodes of the system for the nominal point and when changing a defined decision variable δ (in the range from 0.1 to 0.9) was made. The evaluation was made based on the storage efficiency, volume of the tanks and flows of energy within the system. The storage efficiency in the nominal point reached 45.08%, but was changing in the range from 35.06% (for δ = 0.1) to 63.93% (for δ = 0.9). For the nominal value of δ, equal to 0.5, volume of the low-pressure tank (LPT) was equal to 132,869 m3, while of the high pressure tank (HPT) to 1219 m3. When changing δ these volumes were changing from 101,900 m3 to 190,878 m3 (for LPT), and from 935 to 1751 m3 (for HPT), respectively. Detailed results are presented in the paper and indicate high storage potential of the proposed solution in regions with underground mine infrastructure.

Autonomous Raman amplifiers in multi-band software-defined optical transport networks

A controller architecture for managing multi-band Raman amplification within software-defined optical transport networks is presented. In the perspective of optical fiber network softwarization and disaggregation, this work provides an operative description of a system capable of autonomously handling Raman amplification on a single fiber span, achieving the working point requested by the control plane in terms of mean gain and tilt. The developed architecture is composed of two software modules: the Raman design unit (RDU) and the Raman controller unit (RCU). First, the RDU defines the nominal optimal working point designing the power level configuration of the Raman card pumps according to the required amplification constraints without considering any channel spectral load. Then, due to the telemetry feedback, the RCU performs a tracking operation of the mean gain towards the target one, linearizing the problem at the nominal optimal working point. The fiber physical parameters needed by the controller for correct operation of the system are extracted through a conceived probing procedure. The proposal shows a high degree of adaptability of the defined Raman amplifier to the particular in-field scenario in which it is deployed, also counteracting spectral load modifications. The behavior of the described system is validated by means of an experimental session, confirming the effectiveness of the controller architecture design and the high accuracy achieved in terms of performance.