Robust Design Methodology Research Articles

Robust Pixel Design Methodologies for a Vertical Avalanche Photodiode (VAPD)-Based CMOS Image Sensor.

We present robust pixel design methodologies for a vertical avalanche photodiode-based CMOS image sensor, taking account of three critical practical factors: (i) "guard-ring-free" pixel isolation layout, (ii) device characteristics "insensitive" to applied voltage and temperature, and (iii) stable operation subject to intense light exposure. The "guard-ring-free" pixel design is established by resolving the tradeoff relationship between electric field concentration and pixel isolation. The effectiveness of the optimization strategy is validated both by simulation and experiment. To realize insensitivity to voltage and temperature variations, a global feedback resistor is shown to effectively suppress variations in device characteristics such as photon detection efficiency and dark count rate. An in-pixel overflow transistor is also introduced to enhance the resistance to strong illumination. The robustness of the fabricated VAPD-CIS is verified by characterization of 122 different chips and through a high-temperature and intense-light-illumination operation test with 5 chips, conducted at 125 °C for 1000 h subject to 940 nm light exposure equivalent to 10 kLux.

Solar thermal hot water system in hospitals: Robust design methodology considering uncertainties

The energy yield of solar thermal installations is influenced by local climatic conditions, heating demand, and the efficiency of the system. These factors are affected by uncertainties arising from natural variations and a lack of knowledge. Designers typically address these uncertainties by oversizing the collector area. However, this practice usually leads to high costs, low efficiency, and short service lifetimes of the system. This paper proposes a robust sizing methodology for the solar thermal system used for service hot water preparation in a case-study hospital with a daily average hot water consumption of 8.69 m3. This novel approach incorporates uncertainties through probabilistic simulations, assessing the system’s reliability in achieving a 70% solar fraction design goal. The simulations reveal a mere 22% confidence in the initial deterministic design concerning the solar target and emphasize the importance of thermal insulation, temperature control, and collector cleaning as key factors to reduce performance variability. Although the final revised design outcome requires a 15% increase in the collector area compared to the initial scenario and stricter specifications for control components, pipe insulation, and valve maintenance, it achieves a 90% reliability. In addition, annual carbon emissions and levelized costs of hot water production can be reduced by 18% and 13%, respectively.

A new distributed robust H∞ control strategy for a class of uncertain interconnected large-scale time-delay systems subject to actuator saturation and disturbance

In the realm of large-scale systems, the complexity of controller design has long been exacerbated by the proliferation of decision variables and inherent conservatism. This study introduces a novel approach to address these challenges, presenting a new distributed robust controller design methodology tailored for large-scale systems grappling with disturbances, uncertainties, and actuator saturations. The primary objectives include reducing conservatism, minimizing decision variables, and significantly curtailing computation time. To surmount these hurdles, the research leverages descriptive and reciprocally convex methods, formulating the design procedure using linear matrix inequalities. This enables the adjustment of uncertain parameters and robust disturbance rejection, thereby ensuring stability in large-scale systems. Additionally, a feedback control law is proposed to accommodate saturation constraints and ensure the closed-loop system’s stability. Notably, the effectiveness of the proposed control scheme is demonstrated through the evaluation of a full-car active suspension system, which is partitioned into interconnected subsystems to a large-scale system. Comparative analyses underscore the superior performance and technical advancements offered by the proposed methodology over existing approaches.

LCC-HVDC Frequency Robust Control Strategy Based on System Parameter Identification in Islanded Operation Mode

To enhance the stability of the frequency at the sending terminal of the HVDC island during operation, a novel DC supplemental frequency robust controller is proposed in this paper. The proposed controller utilizes the fast controllability of a DC power supply to maintain system frequency stability. The identification of a low-order linearized model of the system can be obtained from a high-precision Prony algorithm based on the second derivative method (SDM). Subsequently, utilizing a robust design methodology based on linear matrix inequalities, an additional frequency robust controller is devised, striking a balance between optimal performance and robustness. This supplementary frequency robust controller exhibits a straightforward control structure with a modest order, making it readily implementable. Simulation experiments conducted within the PSCAD/EMTDC framework substantiate that the designed supplemental frequency robust controller significantly enhances the frequency stability of the sending terminal system. Furthermore, when compared with traditional proportional integral (PI) controllers, it demonstrates superior control efficacy and robustness against various types of faults under different operational modes. Even in interconnected operational modes, it continues to operate effectively. The research findings offer valuable insights for practical applications in islanded power systems.

Experimental design using the Taguchi method for the development of conductive textiles used in flexible thermoelectric generators

This paper presents several aspects of the robust experimental design methodology using the Taguchi method to develop electrically conductive textiles. These conductive textiles will be used to make thermoelectric generators based on the Seebeck effect. Since the experimental development involves the use of the magnetron sputtering method with more than three variables, the Taguchi method was selected to observe how different parameters (5 independent variables such as argon flow, power, pressure, deposition surface area and metal type used for solid targets) influence the mean and variance of the process performance defined by the thickness of the metal film deposited (dependent variable). In the experimental design framework, the analysis using the Taguchi method, followed by optimisation, helped select the optimal experiments from the set of possible experiments. This methodology reduced the number of experiments by 21–42% and minimised resource consumption (e.g., metal targets, argon, energy).

Robust shape optimization using artificial neural networks based surrogate modeling for an aircraft wing

Aerodynamic shape optimization is a very active area of research that faces the challenges of highly demanding Computational Fluid Dynamics (CFD) problems, optimization with Partial Differential Equations (PDEs) as constraints, and the appropriate treatment of uncertainties. This includes the development of robust design methodologies that are computationally efficient while maintaining the desired level of accuracy in the optimization process. This paper addresses aerodynamic shape optimization problems involving uncertain operating conditions. After a review of possible approaches to account for uncertainties, an Artificial Neural Network (ANN) model is used to approximate the aerodynamic coefficients when the operating conditions vary. Robust optimization problem-solving approaches based on deterministic measurements are used, inspired by the work of Deb [Deb K., Gupta H. Introducing robustness in multi-objective optimization. KanGAL Report 2004–2016, Kanpur Genetic Algorithms Laboratory, Indian Institute of Technology, Kanpur, India (2004)]. The first procedure is a direct extension of a technique used for single-objective optimization. The second is a more practical approach allowing a user to define the desired degree of robustness in a problem. These approaches have been tested and validated in the case of the optimization of an aircraft wing profile in the transonic regime considering two uncertain variables: the Mach number and the angle of incidence.

Infinite Dimensional Design Approach of Robust Disturbance Observer for a Piezo-Actuated Nano-Positioner With Measurement Delays

In this article, we consider the disturbance observer (DOB) design supporting high performance nano-positioning with sensor-induced time delays, where the standard robust disturbance observer design methodology is extended to time-delay systems by employing an infinite dimensional approach. In particular, the dynamic model including the piezo-induced hysteresis and the measurement delays are investigated and the infinite dimensional <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {H}^\infty$</tex-math></inline-formula> optimization problem is formulated to achieve an optimal Q-filter design in the DOB control framework. The fragility resulting from unstable pole-zero cancellations in the infinite dimensional Q-filter is further discussed and the direct-moment-matching-based rational approximation is developed for stable digital implementations of the proposed method. Comprehensive experimental studies are conducted on a piezo-actuated stage, where the proposed method successfully demonstrates excellent performances on hysteresis compensation, disturbance suppression, and trajectory tracking, significantly outperforming existing approaches.

Editorial: Special Issue on Very High Cycle Fatigue

Abstract As the co-guest editors of the special issue of ASTM International’s journal Materials Performance and Characterization on very high cycle fatigue (VHCF), we are delighted to have this issue published by ASTM. Fatigue phenomena have long been a topic of significant interest and of research focusing on understanding the behavior of materials and structures under cyclic loading. However, the exploration of fatigue properties beyond traditional high cycle fatigue has gained substantial momentum in recent years. The VHCF regime, characterized by fatigue life exceeding 107 cycles, presents unique challenges and opportunities for advancing our understanding of fatigue mechanisms and developing robust design methodologies. This special issue brings together a collection of outstanding research articles that delve into various aspects of VHCF and contains 15 peer-reviewed articles (research and review) from researchers all around the globe (Asia, South and North America, and Europe). The published contributions encompass a broad range of materials, including metals and alloys, and employ diverse experimental, analytical, and computational techniques to investigate the behavior of structures subjected to VHCF loading. The research presented here not only enhances our fundamental knowledge of fatigue mechanisms but also provides practical insights for industrial applications such as aerospace, automotive, and additive manufacturing. We would like to sincerely thank all the authors who contributed to this special issue for their high-quality submissions, which greatly contribute to the advancement of this less-explored field. We also extend our acknowledgment to the Editor in Chief of the journal, Dr. Richard W. Neu (Georgia Institute of Technology), and the ASTM Publishing Manager, Ms. Alyssa Conaway. Without their invaluable help and support, it would have been impossible to publish this special issue. We hope this special issue enhances our knowledge and understanding in the field of fatigue, particularly VHCF, and serves as a reliable reference for students, researchers, and engineers working in this field. Co-guest editors Summer 2023

Facilitating entry to land sector carbon abatement projects: the LOOC-C tool

Carbon farming presents an opportunity for the land sector to generate income and transition to more sustainable land management practices. In Australia, establishing a carbon project and earning carbon credits is complex, with project proponents needing to satisfy eligibility requirements and adhere to rigorous measurement, verification, and reporting protocols of approved methods. To address these challenges, a human centered design (HCD) approach was used to deliver a digital solution, serving landowners’ needs related to method discovery and reconfiguring how the methodological and scientific complexity of abatement potentials was delivered. The solution, called LOOC-C (pronounced “Look-see”), supports the discovery of abatement methods that are available for a given land area and provides an initial estimate of the potential quantum of carbon sequestered/emitted and the nature of co-benefits associated with each eligible method. Reporting on LOOC-C development and its observed impact demonstrates the role that human centered digital tools have in promoting land management actions that are both sustainable and reasonable to undertake. It equally demonstrates the power of integrating environmental market and user requirements with a robust design methodology. With similar opportunities in environmental markets globally, additional applications of an HCD approach are proposed.

Kansei engineering with online review mining methodology for robust service design

Kansei Engineering (KE) has shown its prominent applicability in service design and development, focusing on translating and interpreting customers’ emotional needs (Kansei) into service characteristics. It is critical and promising as the services sector has grown faster than the manufacturing sector in developing economies in the past three decades. It accounted for an average of 55% of GDP in some developing economies. KE’s flexibility in collaborating with other methods and covering various service settings shows its unique superiority. However, there is criticism of the collected Kansei’s validity and the proposed solution’s robustness. It might be potentially caused by the dynamics of customer emotional needs and various service settings. As a result, Kansei is found to be somewhat fuzzy, unclear, and ambiguous. Hence, a more structured KE methodology incorporating the Kansei text mining process for robust service design is proposed. Kansei text mining approach will extract and summarize service attributes and their corresponding affective responses based on the online product descriptions and customer reviews. The Taguchi method will support the robustness of the proposed improvement strategy. An empirical study of a zoo as a tourism attraction service and its practical implication is discussed and validated in the proposed integrative framework.

Optimizing Tomato Plant Growth and Yield through Innovative Fertilizer Combinations: A Factorial Group Random Design Approach

This study employed a rigorous Factorial Group Random Design (RAK) method to investigate the synergistic effects of Liquid Complementary Fertilizer (PPC) and NPK Compound Fertilizer on the growth and yield of tomato plants. The research consisted of two key factors: PPC with four dosage levels (control, 3 g/L, 6 g/L, and 9 g/L of water) and NPK Compound Fertilizer with four levels (control, 200 kg/ha, 400 kg/ha, and 600 kg/ha) - all replicated three times. Data on critical plant parameters such as height, leaf count, flower abundance, and fruit production were meticulously gathered and analyzed. Remarkably, the combined application of PPC and NPK exhibited significant enhancements in both growth and yield, surpassing the effects observed from individual applications. Our findings highlight the immense potential of this innovative fertilizer combination in revolutionizing tomato crop production, offering a promising avenue for farmers to meet agricultural demands efficiently.&#x0D; Highlights:&#x0D; &#x0D; Utilized a robust Factorial Group Random Design (RAK) methodology to examine the impact of PPC and NPK Compound Fertilizer on tomato plant growth and yield.&#x0D; Investigated various dosage levels of PPC and NPK, each replicated three times for precise data analysis.&#x0D; The synergistic effects of the combined application outperformed individual applications, showcasing a promising approach to optimize tomato crop production.&#x0D;

Designing multivariable PI controller with multi-response optimization for a pilot plant binary distillation column: a robust design approach

Purpose The purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates multiple responses while considering the process's control and noise parameters. In addition, this paper intended to develop a multidisciplinary approach by combining computational science, control engineering and statistical methodologies to ensure a resilient process with the best use of available resources. Design/methodology/approach Taguchi's robust design methodology and multi-response optimisation approaches are adopted to meet the research aims. Two-Input-Two-Output transfer function model of the distillation column system is investigated. In designing the control system, the Steady State Gain Matrix and process factors such as time constant (t) and time delay (?) are also used. The unique methodology is implemented and validated using the pilot plant's distillation column. To determine the robustness of the proposed control system, a simulation study, statistical analysis and real-time experimentation are conducted. In addition, the outcomes are compared to different control algorithms. Findings Research indicates that integral control parameters (Ki) affect outputs substantially more than proportional control parameters (Kp). The results of this paper show that control and noise parameters must be considered to make the control system robust. In addition, Taguchi's approach, in conjunction with multi-response optimisation, ensures robust controller design with optimal use of resources. Eventually, this research shows that the best outcomes for all the performance indices are achieved when Kp11 = 1.6859, Kp12 = −2.061, Kp21 = 3.1846, Kp22 = −1.2176, Ki11 = 1.0628, Ki12 = −1.2989, Ki21 = 2.454 and Ki22 = −0.7676. Originality/value This paper provides a step-by-step strategy for designing and validating a multi-response control system that accommodates controllable and uncontrollable parameters (noise parameters). The methodology can be used in any industrial Multi-Input-Multi-Output system to ensure process robustness. In addition, this paper proposes a multidisciplinary approach to industrial controller design that academics and industry can refine and improve.

INTEGRATED DESIGN METHODOLOGY: A PROPOSAL FOR A SCIENTIFIC RESEARCH-BASED DESIGN PROCESS FOR STIMULI-RESPONSIVE PRODUCTS

AbstractComplex global problems, such as sustainable crop production, where conventional products do not fully solve the problem due to their low efficacy and negative environmental impact, require rationally designed products. Generally, these products are based on efficient technologies and stimuli-responsive and high-performance materials. Considering the product design approach with a science-based approach such as drug development through QbD. We propose to merge the most relevant elements of these approaches in an integrated design methodology. Regarding the conceptual analysis, we propose two phases: initially, an early phase with conceptual solutions, followed by an advanced phase based on QbD elements to define the research hypothesis. Hence, optimal product conditions defined in the design space must comply with the required performance of the stimuli-responsive product. So, with this proposed integration we pretend to potentialize and strengthen the established tools for product design, achieving an advanced and robust design methodology.

A brighter future? Stable and growing sea turtle populations in the Republic of Maldives.

The Indian Ocean represents a significant data gap in the evaluation of sea turtle population status and trends. Like many small island states, the Republic of Maldives has limited baseline data, capacity and resources to gather information on sea turtle abundance, distribution and trends to evaluate their conservation status. We applied a Robust Design methodology to convert opportunistic photographic identification records into estimates of abundance and key demographic parameters for hawksbill sea turtles (Eretmochelys imbricata) and green sea turtles (Chelonia mydas) in the Republic of Maldives. Photographs were collected ad hoc by marine biologists and citizen scientists around the country from May 2016 to November 2019. Across 10 sites in four atolls, we identified 325 unique hawksbill turtles and 291 unique green turtles-where most were juveniles. Our analyses suggest that, even when controlling for survey effort and detectability dynamics, the populations of both species are stable and/or increasing in the short term at many reefs in the Maldives and the country appears to provide excellent habitat for recruiting juvenile turtles of both species. Our results represent one of the first empirical estimations of sea turtle population trends that account for detectability. This approach provides a cost-effective way for small island states in the Global South to evaluate threats to wildlife while accounting for biases inherent in community science data.

-Synthesis-Based Generalized Robust Framework for Grid-Following and Grid-Forming Inverters

Grid-following and grid-forming inverters are integral components of microgrids and for integration of renewable energy sources with the grid. For grid following (GFL) inverters, which need to emulate controllable current sources, a significant challenge is to address the large uncertainty of the grid impedance. For grid forming (GFM) inverters, which need to emulate a controllable voltage source, large uncertainty due to varying loads has to be addressed. This article presents a generalized control framework by leveraging the voltage-current duality in the plant dynamic model of GFL and GFM inverters. The modeling of uncertainties is also generalized under the control framework by quantifying the uncertainties in grid impedance parameters and the uncertainties in equivalent loading parameters for GFL and GFM inverters, respectively. Based on the generalized control framework, a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{\mu}$</tex-math></inline-formula> -synthesis-based robust control design methodology is proposed for both GFL and GFM inverters. The control objectives, while designing the proposed optimal controllers, are reference tracking, disturbance rejection, and harmonic compensation capability with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${i})$</tex-math></inline-formula> sufficient <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${LCL}$</tex-math></inline-formula> resonance damping under large variations of grid impedance uncertainty for GFL inverters and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${ii})$</tex-math></inline-formula> with enhanced dynamic response under large variations of equivalent loading uncertainty for GFM inverters. A combined system-in-the-loop, controller hardware-in-the-loop, and power hardware-in-the-loop based experimental validation on <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {10}$</tex-math></inline-formula> -kVA microgrid system with two physical inverter systems is conducted in order to evaluate the efficacy and viability of the proposed controllers.

Linear uncertain modelling of LIDAR systems for robust wind turbine control design

Light detection and ranging (LIDAR) sensors measure the free wind ahead of the rotor, enabling the use of new feedforward control strategies. However, there exist some sources of error inherent to the measuring process that should be considered during the design of LIDAR-based controllers. Typically, the coherence function is used for that purpose, but it is not compatible with some robust design methodologies. This paper presents an analytic relation between the coherence function and a non-parametric uncertainty model of LIDAR sensors, suitable for the design of controllers via μ-synthesis or Quantitative Feedback Theory. Such a relation is applied to a realistic LIDAR simulator. First, the linear non-parametric uncertainty model is identified using simulation data obtained from the well-known NREL 5 MW wind turbine. Then, it is validated against the coherence model by comparing linear predictions of the simulation outputs.

Optimization of technological parameters for production of calibrated steel using robust design methodology

The issues of the optimal mode designing for the production of calibrated rolled products made of C10C lowcarbon steel are considered, the purpose of which is to provide the required mechanical properties (tensile strength and reducion of area). The formation process of mechanical properties of calibrated rolled products made of C10C steel in the manufacturing process is studies. An optimal mode for the production of calibrated rolled products made of C10C steel is developed using the robust design methodology. This technological regime allows to ensure the quality of products, taking into account the increased requirements of the consumer.

Clustering Techniques for Stable Linear Dynamical Systems with applications to Hard Disk Drives

In Robust Control and Data Driven Robust Control design methodologies, multiple plant transfer functions or a family of transfer functions are considered and a common controller is designed such that all the plants that fall into this family are stabilized. Though the plants are stabilized, the controller might be sub-optimal for each of the plants when the variations in the plants are large. This paper presents a way of clustering stable linear dynamical systems for the design of robust controllers within each of the clusters such that the controllers are optimal for each of the clusters. First a k-medoids algorithm for hard clustering will be presented for stable Linear Time Invariant (LTI) systems and then a Gaussian Mixture Models (GMM) clustering for a special class of LTI systems, common for Hard Disk Drive plants, will be presented.

Robust lightweight design and digital twins considering manufacturing quality variation and sustainability requirements

In this paper, robustness optimization of a fatigue-critical welded structure with measured misalignments and a generic robust design procedure are presented. The motivation for considering uncertainties, robustness and multi-criteria decision making in engineering design comes from the increasing sustainability requirements. Lightweight design of vehicles can reduce CO2 emissions and increase energy and material efficiency, but often the fatigue of welds limits the weight reduction. The manufacturing quality affects the fatigue strength of welds, and by quantifying the manufacturing quality and using robust design methodology the increasing sustainability requirements can be met, while also considering the technical and economical constraints. The surrogate model representing the relationship between the actual, measured geometry and the fatigue life can be used as the digital twin during operation.

Optimal placement of non-redundant sensors for structural health monitoring under model uncertainty and measurement noise

Dense distribution of sensors for structural health monitoring can supply sufficient – yet redundant – information, especially for sensors with high reliability and excellent quality. The design space is thus classified into several clusters conveying equivalent information to assist in a non-redundant sensor layout and avoid dense distributions. Further, practical issues of model uncertainty and measurement noise should also be considered. Based on the effective independence method, the sensor design problem in this work is formulated with two optimization objectives under model uncertainty and measurement noise. Gaussian process regression model is employed to relieve the computation burden when evaluating two objectives. Accordingly, a methodology for robust design of non-redundant sensors is newly developed for the first time, and demonstrated via application to case studies. Optimized designs disperse sensors in the space and tend to place sensors where small amplitudes of dynamic information are exhibited to be robust with respect to uncertainties.