Continuous Set Research Articles

Low-Ripple Continuous Control Set Model Predictive Torque Control for Switched Reluctance Machines Based on Equivalent Linear SRM Model

In this article, a low-ripple continuous control set (CCS) model predictive torque control (MPTC) method for switched reluctance machines (SRMs) is proposed. The inherent high nonlinearity of the SRMs makes it difficult to solve the optimization problem in the CCS MPTC algorithm analytically. To address this issue, an equivalent linear SRM model is adopted, and the cost function is also properly modified. Then, with the torque boundary values provided by executing the voltage vectors of an improved switching table, the optimization problem in the CCS MPTC method becomes simple and analytically solvable. The Lagrange multiplier method is employed to solve this optimization problem analytically and generate the optimum torque reference values for the active phases. Based on the estimated torque variation rates, the duty cycles for each phase are calculated. Extensive simulation and experimental tests are carried out in a four-phase 8/6 SRM setup. These testing results reveal that the proposed CCS MPTC method shows much lower torque ripples and current ripples in a wide speed range with a low computational burden than the existing finite control set MPTC methods.

Using the Monte Carlo method to determine the volume of excavation work

The article describes a method for calculating the volume of spatial models when performing earthworks. It is based on the Monte Carlo method. The solution of the problem is based on the use of photogrammetric survey and the construction on this basis of a digital model of the surface and a three-dimensional digital model of the result of excavation work. Additionally, a reference three-dimensional object is introduced, covering the volume of excavation work. The dimensions and volume of the reference object are known. A random number sensor with a uniform distribution is used. The method is based on comparing relations of discrete sets and continuous sets. The concept of discrete volume is introduced. Based on comparative estimates of discrete volumes and continuous volumes, the volume of a three-dimensional object is calculated using the known volume of the standard. The method excludes geometric volume calculations for complex configurations of walls and the bottom of a three-dimensional object. The article contains an assessment of the applicability of the method and an estimate of calculation errors.

Nghiên cứu đánh giá tác động của trường thủy động lực đến địa hình đáy biển đảo Nam Yết – Trường Sa

This research assesses the impact of major marine hydrodynamic factors, such as waves, currents, and sea levels on the changing processes of the seabed topography and the coastlines of the Namyit (Nam Yết) Island of Truong Sa (Spratly) Islands, based on a many continuous years-data set. The study uses MIKE model to calculate and simulate the impact of wave field and current field on the process of accretion and erosion that changes the topography of the seabed. The results show that when comparing between calculated wave height, speed of the currents, and sea level height and those observed on scene are 69.1%, 54.5%, and 95.4% respectively. These figures meet the requirement of Nash Sutcliffe Efficiency, in which calculated sea level shows highest reliability. The research results provide an overview of wave and currents regimes in Northeast and Southwest monsoon seasons, and the characteristics of the current seabed topography around Namyit Island. The changing of seabed around Namyit Island includes diversified accretion and erosion. In the area from the depth of 10 m to the Island’ coastlines, the accretion dominant, with sediment thickness of up to 2.0 m. At 200 m West and East of the island, there have erosion areas, with sediment thickness reduces to 1.0 m. The changing of natural seabed topography of the researched area is mainly impacted by the process of accretion and erosion of sediment due to hydrodynamic regimes (waves, currents, and sea levels fluctuations) and the development and decline of seabed coral system. The research results are the scientific basis for planning, and proposing the construction around the island, planning for navigation channels dredging, and providing information for naval training, exercises, and operations around offshore islands.

Quality, Greenness, and Product Line Choices for a Manufacturer With Environmental Responsibility Behaviors

Motivated by the rising environmental protection awareness and the importance of green product design, in this article we develop two models to investigate the quality and greenness decisions and product line choices of a green manufacturer as well as the corresponding impact of product line length on environmental performance. In our models, both the manufacturer and consumers show environmental responsibility behaviors. We find that the manufacturer extends the product line when the unit fit cost, the green cost, the quality cost, the market scale of low-segment consumers, and the environmental responsibility level (or unit environmental cost) are low. In the presence of two products with different market positioning, our analysis reveals that: first, owing to the consumer's self-selection behavior, product quality and greenness may be distorted from the efficient quality and greenness; second, product line extension may improve both the environmental performance and the manufacturer's utility, i.e., achieving a win–win outcome; and third, a higher unit environmental cost (environmental responsibility level or a longer product line) will improve the environmental performance if the unit environmental cost is high. In the continuous green valuation setting, interestingly, we find different results that the manufacturer with a high environmental responsibility level may extend its product line, and the environmental performance increases with the unit environmental cost in the single-product case.

Non-Perturbative Treatment of Open-System Multi-Time Expectation Values in Gaussian Bosonic Environments

We determine the conditions for the equivalence between the multi-time expectation values of a general finite-dimensional open quantum system when interacting with, respectively, an environment undergoing a free unitary evolution or a discrete environment under a free evolution fixed by a proper Gorini-Kossakowski-Lindblad-Sudarshan generator. We prove that the equivalence holds if both environments are bosonic and Gaussian and if the one- and two-time correlation functions of the corresponding interaction operators are the same at all times. This result leads to a non-perturbative evaluation of the multi-time expectation values of operators and maps of open quantum systems interacting with a continuous set of bosonic modes by means of a limited number of damped modes, thus setting the ground for the investigation of open-system multi-time quantities in fully general regimes.

Pengembangan Instrumen Penilaian Hasil Belajar Yang Mendukung Asesmen Kompetensi Minimum (AKM) bagi Guru Matematika SMP

DEVELOPMENT OF LEARNİNG OUTCOMES ASSESSMENT INSTRUMENTS THAT SUPPORT AKM (ASESMEN KOMPETENSI MINIMUM) FOR MİDDLE SCHOOL MATHEMATİCS TEACHERS. The cancellation of the implementation of the UN was realized due to the Covid-19 pandemic that hit in 2020, so it was not possible to carry out the UN with various considerations. Over time, preparations were made to strengthen the AKM and character surveys. The process of developing assessment instruments for junior high school teachers is carried out in a continuous training setting accompanied by experts from universities. Through this service activity for junior high school mathematics teachers, it is possible to collaborate among teachers in various educational units or to develop joint programs for the common good; For example, in professional development. Training and mentoring activities in the development of electronic-based learning outcomes assessment instruments that support AKM have been carried out very well. This is indicated by the results of the response questionnaire of 85% which exceeds the indicators of the success of training and service activities.

Publics and their health: 50years of continuity and change.

This article explores a set of changes and continuities in relation to public health and its publics in the UK since the establishment of the Faculty of Public Health in 1972. The article draws on historical research to produce a synthetic analysis of key changes and continuities in British public health since 1972. Three key areas are identified. The first centres on the issue of who has responsibility for public health. The second examines the persistence of social and racial inequalities in population health. The third considers the 'return' of infectious disease as a threat to public health. Despite the trend to place more responsibility for individual and collective health on the public itself, there was a proliferation in the actors and authorities involved in securing and protecting the health of the public. The strong linkages between health and structural inequality, and the challenges of addressing these, demonstrate that public health never was (and never can be) solely an individual matter. The appearance of new diseases, such as HIV/AIDS and the return of ones thought to have been conquered, like tuberculosis, raised profound questions for public health authorities and the people they cared for.

AI-Based Exhaust Gas Temperature Prediction for Trustworthy Safety-Critical Applications

Data-driven condition-based maintenance (CBM) and predictive maintenance (PdM) strategies have emerged over recent years and aim at minimizing the aviation maintenance costs and environmental impact by the diagnosis and prognosis of aircraft systems. As the use of data and relevant algorithms is essential to AI-based gas turbine diagnostics, there are different technical, operational, and regulatory challenges that need to be tackled in order for the aeronautical industry to be able to exploit their full potential. In this work, the machine learning (ML) method of the generalised additive model (GAM) is used in order to predict the evolution of an aero engine’s exhaust gas temperature (EGT). Three different continuous synthetic data sets developed by NASA are employed, known as New Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS), with increasing complexity in engine deterioration. The results show that the GAM can be predict the evolution of the EGT with high accuracy when using several input features that resemble the types of physical sensors installed in aero gas turbines currently in operation. As the GAM offers good interpretability, this case study is used to discuss the different data attributes a data set needs to have in order to build trust and move towards certifiable models in the future.

The product of two high-frequency Graph Laplacian eigenfunctions is smooth

In the continuous setting, we expect the product of two oscillating functions to oscillate even more (generically). On a graph G=(V,E), there are only |V| eigenvectors of the Laplacian L=D−A, so one oscillates ‘the most’. The purpose of this short note is to point out an interesting phenomenon: if ϕ1,ϕ2 are delocalized eigenvectors of L corresponding to large eigenvalues, then their (pointwise) product ϕ1⋅ϕ2 is smooth (in the sense of small Dirichlet energy): highly oscillatory functions have largely matching oscillation patterns.

Nonparametric Functional Data Analysis for Forecasting Container Throughput: The Case of Shanghai Port

Transportation is one of the major carbon sources in China. Container throughput is one of the main influencing factors of ports’ carbon emission budget, and accurate prediction of container throughput is of great significance to the study of carbon emissions. Time series methods are key techniques and frequently used for container throughput. However, the existing time series methods treat container throughput data as discrete points and ignore the functional characteristics of the data. There has recently been interest in developing new statistical methods to predict time series by taking into account a continuous set of past values as predictors. In addition, to eliminate the linear constraint in the functional time series prediction approach, we propose a functional version of a nonparametric model that allows using a continuous path in the past to predict future values of the process, including functional nonparametric regression and functional conditional quantile and functional conditional mode models, to forecast the container throughput of Shanghai Port. For the purpose better forecasting, an experiment was conducted to compare our functional data analysis approaches with other forecasting methods. The results indicated that nonparametric functional forecasting methods exhibit more significant performance than other classical models, including the functional linear regression model, nonparametric regression model, and autoregressive integrated moving-average model. At the same time, we also compared the prediction accuracy of the three nonparametric functional methods.

Petrogenesis of late Paleoproterozoic post-collisional magmatism in southern north China Craton: Insights from geochemistry and Nd–Hf isotopic compositions of A-type granites

A-type granites are produced commonly in extensional settings and they are important proxies to track breakup of continent. Here we report systematic studies on geochronology and geochemical features of A-type granites in Songxian–Ruyang region, southern margin of the North China Craton (NCC), in order to constrain their petrogenesis and tectonic implications. Zircons from these granites show oscillatory zoning and high Th/U ratios (0.12 to 1.26), indicating a magmatic origin. LA–ICP–MS zircon U–Pb dating shows that they were emplaced at 1813 to 1789 Ma, indicating that they were formed in late Paleoproterozoic. Geochemically, these rocks are high in SiO2 (67.51–74.42 wt%) and total alkalis (Na2O + K2O = 7.76–10.19 wt%), and low in MgO (0.09–1.31 wt%), CaO (0.09–1.11 wt%) and P2O5 (0.12–0.26 wt%) contents, with negative Nb, Ta, Sr, P and Ti anomalies. They are characterized by high FeOT/(MgO + FeOT), 10000 Ga/Al ratios (1.57–3.15) and Zr + Nb + Ce + Y contents (566–835 ppm). They are also characterized by high calculated Zr saturation temperatures (892–918 °C), high Ti-in-zircon temperatures (693–912 °C) and metaluminous to weakly peraluminous natures, which are typical features of aluminous A-type granites, further belonging to the A2 granites. The low zircon εHf(t) values (–13.8 to –8.6), along with the low whole rock εNd(t) values (–8.62 to –6.10) and low apatite εNd(t) values (–8.31 to –6.56), indicate that the Songxian–Ruyang A-type granites were derived from partial melting of the calc-alkaline tonalitic–trondhjemitic–granodioritic gneisses in Taihua Complex, and they were formed in post-collisional extensional setting. Combined with coeval regional granitoids, the south margin of the NCC is in a continuous extensional setting during 1.8–1.6 Ga, and the Songxian–Ruyang A-type granites can represent a response of the breakup of Columbia supercontinent.

Interval-analysis-based determination of the trajectory-reachable workspace of planar cable-suspended parallel robots

This paper proposes an interval-analysis-based algorithm to determine the trajectory-reachable workspace (TRW) of planar two-degree-of-freedom (DOF) cable-suspended parallel robots and planar three-DOF cable-suspended parallel robots. The TRW is a set of target points that the end-effector can reach along a given trajectory under the cable tension constraint. The method includes two sufficient conditions for a continuous set of target points to lie fully inside or outside the TRW. The two conditions can be verified by the implementation of interval-analysis-based methods. On the basis of these two verifiable sufficient conditions, a TRW determination method using branch-and-prune algorithms is presented. This method avoids the discretization of a continuous trajectory set, which guarantees the accuracy of TRW determination. Moreover, this method can determine the TRW when there are small uncertainties regarding the robot geometric parameters . • A new Trajectory-Reachable Workspace (TRW) determination method based on interval analysis. • High accuracy in determination TRW of planar cable-suspended parallel robots. • Computational time advantage in verification that a prescribed workspace belongs to TRW. • Small uncertainties on the geometric parameters can be handled in the determination of TRW.

Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errors.

In reinforcement learning (RL), function approximation errors are known to easily lead to the Q -value overestimations, thus greatly reducing policy performance. This article presents a distributional soft actor-critic (DSAC) algorithm, which is an off-policy RL method for continuous control setting, to improve the policy performance by mitigating Q -value overestimations. We first discover in theory that learning a distribution function of state-action returns can effectively mitigate Q -value overestimations because it is capable of adaptively adjusting the update step size of the Q -value function. Then, a distributional soft policy iteration (DSPI) framework is developed by embedding the return distribution function into maximum entropy RL. Finally, we present a deep off-policy actor-critic variant of DSPI, called DSAC, which directly learns a continuous return distribution by keeping the variance of the state-action returns within a reasonable range to address exploding and vanishing gradient problems. We evaluate DSAC on the suite of MuJoCo continuous control tasks, achieving the state-of-the-art performance.

Linear Parameter Varying Models-Based Gain-Scheduling Control for Lane Keeping System With Parameter Reduction

In this paper, a robust <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {H}_{2}$ </tex-math></inline-formula> controller based on Linear Parameter Varying (LPV) model with scheduling variable reduction is applied for a lane-keeping system. On a curved road section, varying longitudinal speed and roll motion lead to multiple parameter variations in the lateral vehicle dynamics. To trade-off between the complexity of the multiple scheduling variables and the accuracy of the LPV model, an order reducing method by Autoencoder (AE) is performed to obtain a reduced model and diminishes the conservatism of LPV-based controller design. Further, to ensure the continuous convex set membership of the reduced scheduling variables in online test scenarios, the Lipschitz constant of the offline trained neural network (NN) is tightly estimated by solving a Semidefinite Program (SDP). The convex set of local Linear Time-Invariant (LTI) controllers is designed according to the estimated Lipschitz bound of the trained NN. The LPV-based robust <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {H}_{2}$ </tex-math></inline-formula> feedback controller is then designed by solving a set of Linear Matrix Inequalities (LMIs). Numerical simulations with full vehicle dynamics from CarSim are given to demonstrate the performance of the proposed system on various test roads. The continuous finding of the reduced scheduling variable membership is guaranteed in the online tests, and the effectiveness of the proposed method is confirmed with the mean value of lateral offset error reduced by about 50% compared with LTI-based <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {H}_{2}$ </tex-math></inline-formula> controllers.

Temporal Evolutions and Quasiperiodic Variations Present in the Sunspot Number and Group Sunspot Area Data Measured at Kodaikanal Observatory for Solar Cycles 14–24

The Kodaikanal Observatory has made synoptic observations of the Sun in white light since 1904, and these images are sketched on the Stonyhurst grids called Sun charts. These continuous hand-drawn data sets are used for long-term studies of the Sun. This article investigates temporal and periodic variations of the monthly hemispheric sunspot number and sunspot group area for 1905–2016, covering solar cycles 14–24. We find that the temporal variations of the sunspot number and group area are different in each hemisphere and peak at different times of the solar cycle in the opposite hemisphere. For both data sets, Cycle 19 shows maximum amplitude. For the sunspot number time series, Cycle 24 was the weakest, and Cycle 15 for the group area. The existence of double peaks and violation of the “odd–even rule” was found in both data sets. We have studied the periodic and quasiperiodic variations in both time series using the wavelet technique. We noticed that, along with the fundamental mode of the ∼11 yr cycle and polarity reversal period of 22 yr, the sunspot activity data also exhibited several midterm periodicities in the opposite hemispheres, in particular the Rieger-group, and quasi-biennial periodicities. The temporal evolution of these detected quasi-periodicities also differs in the northern and southern hemispheres. We analyzed the data set statistically to understand the bulk properties and coupling between the opposite hemispheres. The study indicates that the two hemispheric data sets differ, but some dependency could be present.

Quadratic Regression Model-Based Indirect Model Predictive Control of AC Drives

Model predictive control is a promising technique for electric drives as it enables optimization for multiple parameters and offers reliable operation with nonlinear systems. In this article, a novel approach is presented that aims to harness the advantages of both finite and continuous set model predictive methods in converter-fed ac drive control. The proposed method requires the calculation of only seven predicted states. These states are then assigned cost function values. Using a quadratic regression model, the cost function is mapped to the entire modulation region. After solving a constrained optimization problem on this cost function mapping, the optimal voltage vector is obtained, which is then applied via pulsewidth modulation. The presented method can also be applied to multilevel converter structures without the need to calculate predictions for additional voltage vectors. Therefore, the proposed method does not increase in complexity with the utilized converter topology. Furthermore, the method offers a fixed switching frequency operation and an exact noniterative solution to the optimization problem due to the formulation of the regression model. As a case study, simulation and experimental results verify the operation of the predictive torque control for permanent magnet synchronous machines with the proposed method.

Multi-type maximal covering location problems: Hybridizing discrete and continuous problems

This paper introduces a general modeling framework for a multi-type maximal covering location problem in which the position of facilities in different normed spaces are simultaneously decided to maximize the demand generated by a set of points. From the need of intertwining location decisions in discrete and in continuous sets, a general hybridized problem is considered in which some types of facilities are to be located in finite sets and the others in continuous normed spaces. A natural non-linear model is proposed for which an integer linear programming reformulation is derived. A branch-and-cut algorithm is developed for better tackling the problem. The study proceeds considering the particular case in which the continuous facilities are to be located in the Euclidean plane. In this case, by taking advantage from some geometrical properties it is possible to propose an alternative integer linear programming model. The results of an extensive battery of computational experiments performed to assess the methodological contribution of this work is reported. Apart from a synthetic dataset, the different approaches are tested on a real geographical and demographic data with up to 920 demand nodes.

Continuous Quantum Gate Sets and Pulse-Class Meta-Optimization

Reducing the circuit depth of quantum circuits is a crucial bottleneck to enabling quantum technology. This depth is inversely proportional to the number of available quantum gates that have been synthesised. Moreover, quantum gate synthesis and control problems exhibit a vast range of external parameter dependencies, both physical and application-specific. In this article we address the possibility of learning families of optimal control pulses which depend adaptively on various parameters, in order to obtain a global optimal mapping from the space of potential parameter values to the control space, and hence continuous classes of gates. Our proposed method is tested on different experimentally relevant quantum gates and proves capable of producing high-fidelity pulses even in presence of multiple variable or uncertain parameters with wide ranges.

Optimal energy performance of dynamic sliding and insulated shades for residential buildings

The paper evaluates the potential energy efficiency benefits for dynamic sliding exterior shades suitable for windows of both new and existing buildings. In particular, the analysis outlined in the paper summarizes the energy performance of dynamic sliding shades when applied to windows for apartment units located in various US climates. A series of sensitivity analyses is performed using a detailed whole-building simulation coupled with modeling techniques of dynamic envelope systems to determine the optimal positions for the dynamic sliding shades to minimize the annual demand for US housing units. Several operation strategies are evaluated using continuous and stepped settings of the positions for the dynamic sliding shades using monthly, daily, and hourly adjustment frequencies. The results of the analyses indicate that the dynamic shades have significant energy efficiency potential for all US climates and design conditions with annual savings in HVAC energy end-use of over 50% especially in hot and mild climates. The performance of the dynamic shades is even higher for large and single-pane windows indicating that these systems can serve as retrofit alternatives to window replacements.

An experimentally driven high-throughput approach to design refractory high-entropy alloys

High-entropy alloy (HEA) design strategies have been limited to theoretical/computational approaches due to their compositional complexity and extremely large compositional parameter space. In this work, we developed an experimentally driven, high-throughput, HEA design approach using a physical vapor deposition (PVD) technique and coupled it with nanomechanical testing to accelerate material design for structural applications. The PVD technique enabled the formation of a compositional gradient across a thin-film sample. Specifically, a 10 cm wafer was used to manufacture a continuous set of 80 HEA compositions within the Nb-Ti-V-Zr family using a single deposition cycle. By using the solid-solution strengthening theory and estimated parameter properties, the strength and ductility of these HEA compositions were quantitatively determined/predicted and then experimentally verified by nano-indentation hardness test. Consequently, 7 refractory HEA compositions were successfully down-selected, which has a high propensity to have a balanced mechanical property.