bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robust Nonlinear Model Predictive Control With Model Predictive Sliding Mode for Continuous-Time Systems
Authors: Hill Elyse , Gadsden S. Andrew , Biglarbegian Mohammad 
Published: November 2021

Abstract
This paper presents a robust, tube-based nonlinear model predictive controller for continuous-time systems with additive disturbances which cascades two sampled-data model predictive controllers: the first creates a desired path using nominal dynamics, and the second maintains the true state close to the nominal state by regulating a sliding variable designed on the error between the true and nominal states. The sampled-data model predictive approach permits easy incorporation of continuous-time sliding mode dynamics, allowing a dynamic boundary layer and tube design to be included. In this way, the control applied to the system capitalizes on the robustness properties of traditional sliding mode control (SMC) while incorporating system constraints. Stability analysis is presented in the context of input-to-state stability (ISS) for continuous-time systems. The proposed controller is implemented on two case studies, is compared to benchmark tube-based model predictive controllers, and is evaluated using average root-mean-square (RMS) values on the state and input variables, in addition to average integral square error (ISE) and integral absolute error (IAE) values on the position states. Results reveal that the proposed technique responds to higher levels of disturbance with significant increases in control effort, eliminates constraint violation by using of constrained SMC as the secondary controller, and maintains similar tracking performance to benchmark controllers at lower levels of control effort.
An Application of Graph Theory for the Detection of Degenerate Structures in Planetary Gear Trains
Authors: Esmail Essam L. , Juber Anahed H. 
Published: November 2021

Abstract
One of the most important steps in the structural synthesis of planetary gear trains is to eliminate degenerate structures. First, the graph theory is used to represent planetary gear trains (PGTs). Second, a procedure is developed to identify fundamental geared entities (FGEs). Further, the single-planet FGEs are shown to have one-DOF and, therefore, cannot constitute a degenerate structure. It is this that allows a significant reduction in the calculation in relation to other methods of diagnosing degenerate structures. Third, using the concepts of FGEs and the notation of the associated adjacency matrix, an algorithm is developed for the detection of degenerate structures in PGTs. The algorithm is based on the fact that any degenerate structure is a PGT formed by two fundamental geared entities with common edges and/or vertices equal to or more than 3. Forth, the concept of connectivity between single-planet FGEs is introduced and a simple, straightforward approach for deducting the connectivity matrix from the adjacency matrix is developed. The new vertex-edge mobility criterion does not require combinatorial analysis. Besides, the method is applicable to one and multiple degrees of freedom PGTs, it is also applicable to multi-planet PGTs and complex PGTs, including contrary examples found in the literature.
Autonomous Transport System With Taxi-Type Automated Guided Vehicles Based on Transport Density
Authors: Nakatani Takuma , Morikawa Daiki , Harada Naoki , Hirogaki Toshiki , Aoyama Eiichi 
Published: November 2021

Abstract
The importance of automated guided vehicles in flexible manufacturing systems is increasing because they can flexibly respond to changes in facilities and factory layouts. Herein, we propose an autonomous conveyance system for automated guided vehicles based on the operation of a taxi transportation system to solve indefinite and accidental problems. The system focuses on the application of traffic engineering knowledge to a flexible taxi transportation system. A taxi is a transport unit in a traffic system, with high adaptability to traveling routes and arrival/departure points. We also propose a task linear density based on transport density, which is an indicator of the scale of transport, such as that of rail transport. We evaluated the efficiency of an automated guided vehicle (AGV) transportation system that introduced waiting and cruising operations, which determine the taxi behavior, using the task linear density. The results indicate that the average matching time and task linear density were negatively correlated and that the transport efficiency improved when the P/Ds were frequently transported to a centralized location.
The Effect of Dynamic Speed Information and Timing of Displaying EHMI on Automated Vehicle and Pedestrian Interactions
Authors: She Jinjuan , Islam Marufa , Zhou Feng 
Published: November 2021

Abstract
Pedestrian-AV (automated vehicle) interaction attracts a significant amount of attention in recent years. However, there are controversial opinions about whether an external human-machine interface (eHMI) that communicates AV’s intent is needed. The authors propose that vehicle built-in cues (e.g., dynamic speed information) and the timing of displaying eHMI when communicating an AV’s yielding intent are both important. An online study was conducted to understand the impact on a 2-way street with a marked but not signalized crosswalk. As predicted, pedestrians were more likely to cross, with higher trust in AV and perceived safety, when the eHMI was displayed earlier. Information of the AV’s decreasing speed did not have a significant effect on crossing decisions, however, it increased trust and perceived safety. In addition, eHMI did have a positive add-on effect on pedestrian’s trust in AV, especially when it was displayed earlier, in the scenarios that dynamic speed of an AV was visible. Moreover, both the timing of eHMI and dynamic speed information played a role in enhancing a pedestrian’s judgment consistency in the short period of the interaction with AV, i.e., viewing the approaching AV from 20 meters away until it stopped near the pedestrian. The study indicated that both information about the vehicle’s physical behavior (i.e., speed) and the eHMI are beneficial in pedestrian-AV communication. More in-depth virtual reality or field studies are needed to further validate the findings.
Environmental and Economic Assessment of a Portable E-Waste Recycling and Rare Earth Elements Recovery Process
Authors: Ohene Opare Emmanuel , Mirkouei Amin 
Published: November 2021

Abstract
Over 40 million tons of electronic devices (e.g., computers, laptops, notebooks, and cell phones) became obsolete in 2020, and this estimate is expected to grow exponentially, mainly due to the decreasing lifespan of electronics. Most of the electronics replaced end up in municipal landfills. Electronic waste (e-waste) has raised concerns because many components in these products are not biodegradable and are toxic. Some of the toxic materials and chemicals include rare earth elements (REEs), which are currently experiencing supply constraints. This study focuses on generated e-wastes from households due to the high amount of these wastes. Technologies for e-waste mining must be tailored to household needs rather than large-scale industrial processes. The use of portable e-waste recovery systems may produce win-win outcomes where industry, households, and regulatory bodies could benefit, and this will incentivize e-waste mining for all stakeholders. This study investigates the sustainability benefits of employing a portable e-waste recycling and REEs recovery, using techno-economic and life cycle assessment methods. The results indicate that the proposed approach in this study mitigates environmental impacts when maleic acid is used as one of the key ingredients in recovering and separating REEs and other metals. It is concluded that when adopted globally, this technology can significantly address the e-waste challenge while improving the availability of REEs for high-tech applications.
Digital Twin Technology for Modeling, Simulation and Control of a Mechatronic System
Authors: Calderon Carrion Mauricio Rafael , Viola Jairo , Chen YangQuan , Visioli Antonio 
Published: November 2021

Abstract
Digital transformation involves the use of breaking technologies that increase the knowledge of a physical system. One of these technologies is the Digital Twin, which is a realistic virtual representation that reflects the current conditions of a physical system process that allows advanced and more detailed analysis towards improving system performance and smartness. This paper uses a novel framework for developing Digital Twin applications, which is applied to the velocity and position control problem. The framework involves the steps of target system definition, system documentation, multidomain simulation, Digital Twin assembly and behavioral matching and validation and deployment. Obtained results show how Digital Twin enables new capabilities that can be explored towards smart control engineering.
Fast Two-Scale Analysis via Clustering
Authors: Yuan Chongxi , Liu Xingchen 
Published: November 2021

Abstract
Both man-made and natural materials exhibit heterogeneous properties at smaller observation scales. The multiscale analysis allows the inclusion of fine-scale information in coarse-scale simulations. One of the commonly used methods is homogenization, replacing the detailed fine-scale structures with their locally homogeneous effective material properties. When fine-scale material structures are stationary, representative volume elements (RVE) are often identified for their effective material properties to be applied over the entire structure. However, in non-stationary material structures, it is inappropriate to assume a single representative material. In this case, homogenization is often required for every individual cell, resulting in significant increases in computational cost.
We propose a stiffness-based clustering algorithm that reduces the total number of homogenization computations needed for multiscale analysis. Cells with similar effective stiffness tensors are clustered together such that only a single homogenization is required for each cluster. Specifically, the clustering algorithm is based on the novel concept of Eigenstiffness, which represents the relative directional stiffness of a given material structure. The rotation invariant property of Eigenstiffness allows material structure with similar intrinsic stiffness but different orientations to be clustered together, further decreasing the number of clusters required for the multiscale analysis. Without a priori knowledge of the accurate homogenized material properties, approximated elasticity tensors and Eigenstiffness estimated through FFT-based homogenization methods are used for rapid clustering. The effectiveness of the method is verified by numerical simulations on various multiscale structures, including Voronoi foams and fiber-reinforced composites.
Towards a Synthesis Method of Kresling Tower Used as a Compliant Building Block
Authors: Berre John , Geiskopf Francois , Rubbert Lennart , Renaud Pierre 
Published: November 2021

Abstract
In this paper, the use of the Kresling tower origami as a building block for compliant mechanism design is considered. Two contributions are introduced to develop a synthesis method of such a building block. First, models to link the origami pattern geometry to the Kresling tower kinematics are derived. The position of stable configurations, the lead angle of its helical motion are expressed as functions of the pattern parameters. Experimental validation of the models is performed. Second, a modification of pattern by local adjustment of fold geometry is introduced. This aims at modifying the origami stiffness without affecting the kinematics. The use of modified fold geometries is experimentally investigated. The capacity to strongly modify the stiffness level is observed, which is encouraging to go towards a synthesis method with decoupling of kinematics and stiffness selection.
On the Mechanical Behaviour in Stiffness Compensated Piezoelectric Beams - An Experimental Investigation Towards Energy Harvesting
Authors: van de Wetering E. , Blad T. W. A. , van Ostayen R. A. J. 
Published: November 2021

Abstract
In this work, a piezoelectric beam is stiffness compensated through adding a negative stiffness formed by attracting magnets. The mechanism’s purpose is low-frequency energy harvesting. The effect of deformation speed on the beam’s stiffness is investigated by force-displacement measurements taken at different speeds and with different load resistors connected. The effect of the load resistance on the beam’s stiffness has been found to be strongly dependent on the deformation speed. A load that results in the same stiffness as in a closed circuit at low deformation speed results in a stiffer response at a faster deformation speed. Also, when the beam is brought close to static balance with a certain load resistance connected, alteration of the load resistance has a great influence on the attained stiffness level. Furthermore, memory effects in the hysteresis found in piezoelectric actuators, related between input voltage and displacement, were also confirmed between displacement and force in sensor application.
A Mirror-Symmetrical XY Compliant Parallel Manipulator With Improved Performances Without Increasing the Footprint
Authors: Zhu Jiaxiang , Hao Guangbo , Li Shiyao , Yu Shuwen , Kong Xianwen 
Published: November 2021

Abstract
The design of XY compliant parallel manipulators (CPMs) remains challenging considering the tradeoff between the mirror-symmetry for better constrained undesired rotations and the small footprint, although a significant number of XY CPMs have been reported in extensive applications. This paper presents a new XY CPM using mirror-symmetry without increasing its footprint, mainly aiming to reduce the undesired parasitic rotations of input and output motion stages. The concept of higher degree of stiffness centre symmetry is deployed to tackle the parasitic rotations, leading to a multi-layer compact XY CPM design with each layer being a rotation-symmetrical design. A nonlinear and analytical model of the proposed XY CPM is derived using free body diagrams and the Beam Constrained Model (BCM) to accurately analyse its performance characteristics over a large range of motion. The designed XY CPM is then verified by the nonlinear finite element analysis (FEA) method. Finally, the proposed multi-layer design is comprehensively compared with the well-received single-layer rotation-symmetrical design. It is shown in the new design that the parasitic rotations of input and output stages along with the actuator isolation are significantly reduced and that the out-of-plane-stiffness is also significantly increased.
Automatic Differentiation in Automatic Generation of the Linearized Equations of Motion
Authors: Minaker Bruce , González Francisco 
Published: November 2021

Abstract
In the ongoing search for mathematically efficient methods of predicting the motion of vehicle and other multibody systems, and presenting the associated results, one of the avenues of continued interest is the linearization of the equations of motion. While linearization can potentially result in reduced fidelity in the model, the benefits in computational speed often make it the pragmatic choice. Linearization techniques are also useful in modal and stability analysis, model order reduction, and state and input estimation. This paper explores the application of automatic differentiation to the generation of the linearized equations of motion. Automatic differentiation allows one to numerically evaluate the derivative of any function, with no prior knowledge of the differential relationship to other functions. It exploits the fact that every computer program must evaluate every function using only elementary arithmetic operations. Using automatic differentiation, derivatives of arbitrary order can be computed, accurately to working precision, with minimal additional computational cost over the evaluation of the base function. There are several freely available software libraries that implement automatic differentiation in modern computing languages. In the paper, several example multibody systems are analyzed, and the computation times of the stiffness matrix are compared using direct evaluation and automatic differentiation. The results show that automatic differentiation can be surprisingly competitive in terms of computational efficiency.
Design of Path Tracking Controller for Autonomous Vehicles Through Bias Learning of Vehicle Dynamic Models Under Environmental Uncertainty
Authors: Ren Lichuan , Xi Zhimin 
Published: November 2021

Abstract
Path tracking error control is an important functionality in the development of autonomous vehicles when a collision-free path has been planned. Large path tracking errors could lead to collision or even out of the control of the vehicle. Vehicle dynamic models are used to minimize the vehicle path tracking error so that control strategies can be designed under different scenarios. However, the vehicle dynamic model may not truly represent the actual vehicle dynamics. Furthermore, the nominal parameter employed in the vehicle dynamic model cannot represent actual operating conditions of the vehicle under environmental uncertainty. This paper presents a learning-based bias modeling method to improve the fidelity of any baseline vehicle dynamics model so that effective path tracking controller design can be achieved through a low fidelity but high-efficiency vehicle dynamic model with the aid of a few experiments or high fidelity simulations. The state-of-the-art of machine learning models, such as Gaussian process (GP) regression, recurrent neural network (RNN), and long short-term memory (LSTM) network, are employed for bias learning and comparison. A high-fidelity vehicle simulator, CARLA, is employed to collect virtual test data and demonstrate the effectiveness of the proposed bias-learning based control strategies under environmental uncertainty.
Design and Actuation of a Skeleton for a Robotic Fish
Authors: Abulon Dina Joy K. , Li Jiaji , McCarthy J. Michael 
Published: November 2021

Abstract
In this paper, we present the design of a pneumatically actuated skeleton for a robotic fish. The tail is designed as a one degree of freedom coiling truss that is actuated by air pressure supplied to pouch actuators along the truss. We present that kinematic synthesis procedure, the fabrication and testing of the fish tail system. Our goal is an efficient and effective fish-like locomotion system.
Research on the Potential of Front Wheel Steering Control for Vehicle Dynamics Control
Authors: Zheng Sheng , Cheng Yiming , Yu Liangyao 
Published: November 2021

Abstract
The development of active steering control technology not only provides key actuators for intelligent vehicle motion control, but also expands vehicle stability and safety. This paper studies the potential control ability of the front-wheel steering control to the vehicle plane dynamics, and the controllable area boundary is designed on the phase plane of side slip angle and yaw rate. Previous studies have defined a dynamics stable area on the vehicle states phase plane, in which the vehicle state can autonomously return to a stable equilibrium point. The area outside the stable area are divided into the controllable area and the uncontrollable area in this paper. In the controllable area, the front-wheel steering control has the ability to pull the vehicle states back towards the stable area. Considering actuator constraints and model errors, based on the principle of safety design, a band-shaped critical area is designed to separate the controllable area from the uncontrollable area, and the linear mathematical model of the controllable area boundary is designed. In order to verify the rationality of the controllable area definition, nonlinear model predictive controller is designed to control the vehicle outside the dynamics stable area. The controller uses the high-fidelity nonlinear vehicle model and the magic formula tire model as the state equation constraints, and the practical steering actuator constraints are used as the control input constraints, and the nonlinear numerical optimization solver is used to solve the optimal steering input sequence. The phase plane analysis of the controlled vehicle verifies the rationality of the controllable area defined in this paper.
Thermal Modeling Using Two-Port Network Impedance Fractional-Order Approximations
Authors: Duhé Jean-François , Victor Stéphane , Melchior Pierre , Abdelmounen Youssef , Roubertie François 
Published: November 2021

Abstract
Sufficiently accurate thermal modeling is necessary for many applications such as heat dissipation, melting processes, building design or even bio-heat transfers in surgery. Circuit models help modeling heat transfer dynamics: this method is simple and is often used to model thermal phenomena. However, such models well approximates low and high frequency behavior but they are not accurate enough in the middle band of interest, thus lacking of precision in dynamical terms. A more complete and accurate description of conductive heat transfer can be obtained by using a two-port network. The resulting analytical expressions are complex and nonlinear in the frequency ω. This complexity in the frequency domain is difficult to handle when it comes to control applications and more specifically in real-time applications such as surgery. Consequently, an analysis of this thermal two-port network in the frequency domain directly leads to fractional-order systems. A frequency domain analysis of the series and shunt impedances will be presented and different approximations will be explored in order to obtain simple but sufficiently precise linear fractional transfer function models. The series impedances are approximated by using asymptotic and pole-zero approximations and the shunt impedance is approximated by using a capacitance approximation and two fractional model approximations.
If a Picture is Worth 1000 Words, Is a Word Worth 1000 Features for Design Metric Estimation?
Authors: Edwards Kristen M. , Peng Aoran , Miller Scarlett R. , Ahmed Faez 
Published: November 2021

Abstract
A picture is worth a thousand words, and in design metric estimation, a word may be worth a thousand features. Pictures are awarded this worth because of their ability to encode a plethora of information. When evaluating designs, we aim to capture a range of information as well, information including usefulness, uniqueness, and novelty of a design. The subjective nature of these concepts makes their evaluation difficult. Despite this, many attempts have been made and metrics developed to do so, because design evaluation is integral to innovation and the creation of novel solutions. The most common metrics used are the consensual assessment technique (CAT) and the Shah, Vargas-Hernandez, and Smith (SVS) method. While CAT is accurate and often regarded as the “gold standard,” it heavily relies on using expert ratings as a basis for judgement, making CAT expensive and time consuming. Comparatively, SVS is less resource-demanding, but it is often criticized as lacking sensitivity and accuracy. We aim to take advantage of the distinct strengths of both methods through machine learning. More specifically, this study seeks to investigate the possibility of using machine learning to facilitate automated creativity assessment. The SVS method results in a text-rich dataset about a design. In this paper we utilize these textual design representations and the deep semantic relationships that words and sentences encode, to predict more desirable design metrics, including CAT metrics. We demonstrate the ability of machine learning models to predict design metrics from the design itself and SVS Survey information. We demonstrate that incorporating natural language processing (NLP) improves prediction results across all of our design metrics, and that clear distinctions in the predictability of certain metrics exist. Our code and additional information about our work are available at http://decode.mit.edu/projects/nlp-design-eval/.