bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anti-Hair Snare Pool Drain Cover
Authors: Barnett Ralph L. , Poczynok Peter J. 
Published: November 2021

Abstract
A drain cover for swimming pools, spas and hot tubs has been designed which addresses eight hazards associated with conventional drain systems. This new drain cover, illustrated in Figure 1, eliminates hair entanglement, child evisceration and finger entrapment as well as minimizing body entrapment. Furthermore, its design and construction provide effective countermeasures against vandalism, broken drain covers, missing drain covers and structural deterioration due to environmental antagonists. Additional features unrelated to safety include a universal fastening system which adapts the cover to all circular main drains available in the United States. Also, the drain cover is an order of magnitude stronger than its competitors and has a safe flow rate that is 37% greater than its nearest competitor’s. The product has been manufactured using a PVC material that is the most resistant formulation currently known for counteracting the effects of ultraviolet radiation and chlorine and other chemicals typically found in pools. This paper presents an anatomy of the product’s development.
Development of Intelligent Hierarchical Control for a Hydraulic Manipulator
Authors: Rahbari Roya , deSilva Clarence W. 
Published: November 2021

Abstract
This paper presents the development of a hierarchical intelligent controller for a hydraulic manipulator, which has been designed to be an integral part of an automated machine for mechanical processing of salmon. The developed controller for this hydraulic actuator is a three-layer hierarchical system. In the bottom layer of the hierarchy, a conventional proportional plus derivative (PD) controller is used to control the position of the cutting blade. The middle layer monitors the performance of the manipulator, preprocesses the response signals, and extracts the performance parameters, based on a step-input response. The top layer infers the tuning actions for the PD servo. The knowledge base for tuning the low level controller has been developed and represented by fuzzy rulesbase modules. The development of this hierarchical control system is discussed and some experimental results are given.
Experimental Joint Control Studies With a Flexible Two-Link System
Authors: Xu Wenwei , Zhang Xiaoping , Nair Satish S. 
Published: November 2021

Abstract
This paper investigates experimentally an adaptive control design for a flexible two-link system considering joint angle control in the presence of system uncertainties. The system uncertainties are treated as unknown bounded continuous functions of the states and a Gaussian network is used to map the uncertainties. Experiment results show the effectiveness of the proposed learning control strategy.
Neural-Based Remote Health Assessment and Failure Diagnostics
Authors: Shoureshi Rahmat A. , Terry Benjamin 
Published: November 2021

Abstract
As industrial competition intensifies, and more emphasis is placed on increased productivity and cost reduction, the development of a means to automatically monitor and assess the health of plant equipment becomes more important. This paper presents results of our research that integrates advances in the use of feature extraction, artificial neural networks, and communication/networking techniques for remote health assessment and failure diagnostics of laboratory and industrial rotating machinery. The key features of this effort are the ability to use internet for remote diagnostics, and combined Welch’s transformation and neural networks for signature creation and analysis.
Singular Value Decomposition of Road Events Into Characteristic Shapes
Authors: Ferris John B. 
Published: November 2021

Abstract
Road profiles are typically characterized by their spectral content. It has been noted by several researches, however, that road profiles are generally nonstationary signals that contain significant irregularities such as potholes. Such signals are not well described in the spectral domain. The objective of this work is to describe road profiles in the spatial domain by developing a set of characteristic shapes onto which individual events can be cast. A set of analytical functions describing these shapes is also developed.
In order to develop a set a characteristic shapes, more than a million events are investigated from a mixture of road types (from highways to gravel roads) and a variety of locations throughout the United States. A set of characteristic shapes is developed for each road type and location. Although the events were drawn from diverse samples, the resulting sets of characteristic shapes are nearly indistinguishable. This similarity allows a single set of characteristic shapes to describe events for a wide class of roads. Variations in these sets are discussed and used in deriving a set of orthogonal analytical functions that describe the characteristic shapes. Individual road events are then mapped onto this set of characteristic shapes. The implications of decomposing road events into these characteristic shapes are discussed.
A New Model of Improved Accuracy for the Dynamic Behavior of Spur Gears
Authors: Spitas Christos A. , Costopoulos Theodore N. 
Published: November 2021

Abstract
A new model of improved accuracy is proposed for the simulation of the dynamic behavior of a pair of spur gears that are free from manufacturing and mounting errors. The load-induced expansion of the actual path of contact with the occurrence of tooth edge contact is taken into account in order to better explain the tooth load sharing process near the lowest and highest point of single tooth contact (LPSTC, HPSTC). In addition, an accurate friction model is utilised and the effect of elastohydrodynamic lubricant film formation on gear vibration is taken into account. Simulation results are extracted for various operating speeds and an evaluation of the proposed model is conducted. The model is constructed in a modular fashion and can consequently be used as a building block for larger mechanisms, such as gear trains and multi-stage gearboxes.
The Influence Region Analysis for the Delayed Resonator Vibration Absorber
Authors: Grillo Giulio , Olgac Nejat 
Published: November 2021

Abstract
This paper presents an influence region analysis for an actively tuned vibration absorber, the Delayed Resonator (DR). DR is shown to respond to tonal excitations with time varying frequencies [1–3]. The vibration suppression is most effective at the point of attachment of the absorber to the primary structure. In this study we show that proper feedback control on the absorber can yield successful vibration suppression at points away from this point of attachment. The form and the size of such “influence region” strongly depend on the structural properties of the absorber and the primary system. There are a number of questions addressed in this paper:
a) Stability of vibration absorption, considering that a single absorber is used to suppress oscillations at different locations.
b) Possible common operating frequency intervals in which the suppression can be switched from one point on the structure to the others.
A three-degree-of-freedom system is taken for as example case. One single DR absorber is demonstrated to suppress the oscillations at one of the three masses at a given time. Instead of an “influence region” a set of “influence points” is introduced. An analysis method is presented to find the common frequency interval in which the DR absorber operates at all three influence points.
Optimization of the Sound Source Position for Shaping Acoustically-Structurally Coupled Cavities
Authors: Sorguc Arzu Gonenc , Hagiwara Ichiro , Shi Qinzhong , Akagunduz Haldun 
Published: November 2021

Abstract
In this study, sound field inside acoustically-structurally coupled rectangular cavity excited by structural loading and sound sources is shaped by optimizing the position of the sound source. In the optimization, Most Probable Optimal Design (MPOD) based on Holographic Neural Network is employed and the results are compared with Sequential Quadratic Programming (SQP). It is shown that source position, rather than source strength, is more effective in acoustically controlled modes. The nodal positions for in-vacuo acoustical normal modes are good candidates for initial starting points.
Motion Synchronization for Multi-Cylinder Electro-Hydraulic System
Authors: Sun Hong , Chiu George T.-C. 
Published: November 2021

Abstract
This paper presents a nonlinear control algorithm to address the motion synchronization problem for a multi-cylinder electro-hydraulic (EH) system. A 2-step design approach is applied such that it utilized linear MIMO robust control technique to design an outer loop motion synchronization controller. A nonlinear SISO perturbation observer based pressure/force controller is designed for each of the lift cylinder as the inner loop controller to handle the nonlinearities associated with the EH actuators. Experimental results on a 4-cylinder system are presented to verify the effectiveness of the proposed approach.
Gear Fatigue Crack Size Estimation Using Embedded Modeling
Authors: Li C. James , Lee Hyungdae , Choi Suk Hwan 
Published: November 2021

Abstract
This paper describes an embedded modeling methodology for identifying gear meshing stiffness from measured gear angular displacement or transmission error (which is the difference between where the gear tooth is physically and where it should be if the gear was perfect). An embedded model integrating a physical based model of the gearbox and a parametric representation, in the form of truncated Fourier series, of meshing stiffness is established. A solution method is then used to find the meshing stiffness that minimizes the discrepancy between model output and the measured output. Furthermore, an algorithm is also developed to estimate the size of tooth crack from identified meshing stiffness. Both simulation and experimental studies were conducted to evaluate if identified tooth meshing stiffness can reveal a tooth crack effectively, and if the crack size can be estimated with adequate level of accuracy.
Novelty Detection Using Auto-Associative Neural Network
Authors: Sohn Hoon , Worden Keith , Farrar Charles R. 
Published: November 2021

Abstract
The primary objective of novelty detection is to examine if a system significantly deviates from the initial baseline condition of the system. In reality, the system is often subject to changing environmental and operation conditions affecting its dynamic characteristics. Such variations include changes in loading, boundary conditions, temperature, and humidity. Most damage diagnosis techniques, however, generally neglect the effects of these changing ambient conditions. Here, a novelty detection technique is developed explicitly taking into account these natural variations of the system in order to minimize false positive indications of true system changes. Auto-associative neural networks are employed to discriminate system changes of interest such as structural deterioration and damage from the natural variations of the system.
Non-Disruptive Online Identification of Linearly Parametrized Systems
Authors: Tarraf Danielle C. , Asada H. Harry 
Published: November 2021

Abstract
The subject of this paper is online identification of systems described by linearly parametrized models, under the assumption that the parameters in question are slowly time varying, and with the requirement that the normal operation of the system is left completely undisturbed by the estimation procedure. A Lyapunov-based parameter estimator design for a class of LP systems is presented, assuming that we have no control over any of the system inputs, including control inputs. The estimation is guaranteed to converge provided good knowledge of extreme scenarios is available and provided certain observability-like requirements, derived in the paper, are met. The proposed design procedure is interpreted in the light of observer design for an ‘envelope’, augmented system where the parameters to be estimated are treated as slow state variables. Illustrative numerical examples follow; Good performance is observed both for the idealized case and for the case where sensor noise is present.
Adaptive Control for Nonlinear Matrix Second-Order Systems With Sign-Varying Damping and Stiffness Operators
Authors: Chellaboina VijaySekhar , Haddad Wassim M. , Hayakawa Tomohisa 
Published: November 2021

Abstract
A direct adaptive control framework for a class of nonlinear matrix second-order dynamical systems with state-dependent uncertainty is developed. The proposed framework guarantees global asymptotic stability of the closed-loop system states associated with the plant dynamics without requiring any knowledge of the system nonlinearities other than the assumption that they are continuous and lower bounded. Generalizations to the case where the system nonlinearities are unbounded are also considered. In the special case of matrix second-order systems with polynomial nonlinearities with unknown coefficients and unknown order, we provide a universal adaptive controller that guarantees closed-loop stability of the plant states.
Modeling and Analysis for Thermal Control of Spindles for Reconfigurable Machines
Authors: Stein Jeffrey L. , Harder John E. 
Published: November 2021

Abstract
Control of thermally induced bearing loads remains an important but unsolved problem for precision, high-speed, metal cutting, machining spindles. Spindle dynamic performance, as well as spindle life, depends on bearing loads. Because these loads can change drastically with a change in process conditions, poor spindle dynamic performance, and dramatically reduced bearing life can result. The purpose of this paper is to evaluate the feasibility of controlling bearing loads by controlling the heat generated by a thermal actuator placed around the housing of the spindle. A mathematical model of the open loop response of a laboratory prototype spindle is developed and validated. The model is then used to evaluate the closed loop performance.
The results show that closed loop control of the bearing load is achievable in steady state and under bandwidth limited transient conditions. The proposed system has reasonable command authority when additional heat is required, however, it is possible for the system to lose control when the heater is required to “provide” negative heat. This situation can be mitigated by proper choice of initial preload. As expected, measurement noise limits the control gain but is not a limiting factor. More open loop tests are suggested to validate the model under a broader set of conditions. In addition, closed loop validation is suggested. However, based on results obtained it appears bearing load control is achievable by controlling the thermal field around the spindle.
Input Profiling for Injection Molding by Reinforcement Learning
Authors: Wang Fan , Dong Shaoqiang , Danai Kourosh , Kazmer David O. 
Published: November 2021

Abstract
An adaptation method is investigated for improving the shape of input profiles in injection molding. The noted characteristic of injection molding is that performance feedback (i.e., part quality measure) becomes available only at the end of the cycle, therefore, the performance of the entire sequence of inputs that form the profile is evaluated by the same delayed measure at the end of the cycle. The proposed profiling method uses the concept of reinforcement learning, which is particularly suited to problems with delayed feedback. For an initial study, the method is tested in improving the profiles of the ram velocity and packing pressure. For this study, a simulation program is used to provide estimates of digital video disks (DVDs) quality attributes as feedback for evaluating the performance of the adapted profiles. The initial results indicate that the proposed method is effective in refining the profiles, which will lead to better quality parts with faster cycles.
Fault Diagnostic System Design Using LMIs, With Applications to Health Monitoring for GPS-Based Lateral Vehicle Control
Authors: Rajamani Rajesh , Shrivastava Ankur 
Published: November 2021

Abstract
This paper develops an explicit design methodology for development of observer-based sensor health monitoring systems using Linear Matrix Inequalities. The developed methodology applies to linear parameter-varying systems with three or more sensors in which the state is observable through any one of the sensors. A fault in any of the system sensors can be uniquely identified by the diagnostic system.
The developed methodology is applied to health monitoring of the lateral sensors on a GPS-controlled truck. A set of three sensors on the truck consisting of a GPS system, a lateral accelerometer and a yaw-rate gyroscope is considered. The performance of the fault diagnostic system is documented from extensive experimental results. Experimental results show that the fault diagnostic system can correctly detect a failure in any of the 3 sensors and accurately identify the source of the fault.
Robust Fault Classification and Handling for Longitudinal Vehicle Control
Authors: Song Bongsob , Howell Adam , Hedrick Karl 
Published: November 2021

Abstract
In this paper, a method of analyzing the performance loss caused by faults that effect the longitudinal control of an automated vehicle is presented. First, a hybrid longitudinal controller based on Dynamic Surface Control (DSC) is developed to provide robust stabilization. Then, ellipsoidal approximations of the tracking error bounds are obtained via convex optimization for the nonlinear closed-loop system. The bounds are then used to design a fault classification scheme and fault management system based on the amount of performance loss as measured by a quadratic Lyapunov function. Simulation results of the fault tolerant controller are shown for both single and multiple multiplicative faults.
Multi-Modal Diagnostics for Vehicle Fault Detection
Authors: Schwall Matthew L. , Gerdes J. Christian 
Published: November 2021

Abstract
On-board vehicle diagnostic systems must have low development and hardware costs in order to be viable. Model-based methods have shown promise since they use analytical redundancy to reduce costly physical redundancy. However, these methods must also be computationally efficient and function accurately even with simple, low-cost models.
The approach presented in this paper uses multiple simple models to analyze dissimilar observable modes of a system. Residuals generated using the models are related and interpreted in a Bayesian network to determine fault probabilities and yield a diagnosis. The technique is demonstrated with a diagnostic system for automobile handling.
Sway Suppression of Suspended Payloads With Hoisting Using Digital Filters
Authors: Economou D. , Antoniadis I. 
Published: November 2021

Abstract
A method is proposed for the suppression both of the transient as well as the residual sway of suspended payloads, including also cases where hoisting occurs during the payload transfer motion. The proposed method is based on the preconditioning of the inputs to the system by digital filtering the input function. Conventional FIR or IIR digital filters can be used for the preconditioning approach. The method is demonstrated in the case of a suspended load carried by a gantry crane. Extensive simulation results clearly verify the effectiveness of the approach.
Uncalibrated Vision-Based Control of Two-Wheeled Mobile Robots
Authors: Piepmeier Jenelle Armstrong , Morgan Peter A. 
Published: November 2021

Abstract
An quasi-Newton method with Jacobian estimation is used to control a mobile robot utilizing visual feedback. The method is uncalibrated, requiring no camera calibration or known robot kinematics. Given a proper task configuration, the robot can be controlled such that it follows a moving target. This paper investigates the appropriate task configurations that result in a controllable system.
Technologies in Surgical Robotics
Authors: Belligundu Sunil , Shiakolas Panayiotis S. 
Published: November 2021

Abstract
This paper presents a partial review of in-use, experimental or under development robotics technology applications in the medical field. The scope of the paper was narrowed by focusing on technologies related to surgical robotics, and applied to surgical procedures for Orthopedics, Telesurgery, Minimally Invasive Surgery, Endoscopy and Neurosurgery. Results of the review revealed that robotics in surgery are correctly considered as a tool for enhancing, not replacing the surgeon’s capabilities. Robotics technology is slowly but steadily gaining acceptance and usage in the field of surgery, but still faces many challenges. Rapid and continuous improvements in robotic technologies have great potential in advancing robotics use in the surgical field.
Integration of Smart Actuators in the Structure of Robots for High-Speed and Precision Object Manipulation
Authors: Rastegar Jahangir S. , Yuan Lifang 
Published: November 2021

Abstract
A systematic method is presented for optimal integration of smart actuators into the structure of robot manipulators for the purpose of enabling them to perform smooth object manipulation with smooth actuated joint motions. Here, the motions are considered to be smooth if they do not contain high harmonic components. For optimal positioning of smart actuators in the structure of robot manipulators, a method is developed based on the evaluation of the transmissibility of displacement (velocity and/or force) from the smart actuators to the robot manipulator joint motions and the end-effector displacements (velocity and/or force). A method is then presented for synthesizing actuated joint and object motions to achieve trajectories that do not contain high harmonic components. By minimizing the high harmonic components of the required joint and object motions with properly sized and placed smart actuators, such computer-controlled machines can operate at relatively higher speeds and achieve greater tracking precision with minimal vibration and control problems. A number of numerical examples are provided.
Sensor-Based Coverage for Demining: Exact Cellular Decompositions and Uncertain Detectors
Authors: Choset Howie , Acar Ercan U. , Zhang Yangang , Schervish Mark 
Published: November 2021

Abstract
Coverage path planning is the determination of a path that a robot must take in order to pass itself, a detector, or some other effector over each point in an environment. Applications include demining, floor scrubbing, and inspection. In previous work, we developed the boustrophedon cellular decomposition, an exact cellular decomposition approach, for the purposes of coverage. Each cell in the boustrophedon decomposition is covered with simple back and forth motions. Therefore, coverage is reduced to finding an exhaustive path through a graph that represents the adjacency relationships of the cells in the boustrophedon decomposition. Such a path will ensure that a detector passes over all points in the environment, but it does not guarantee that all ordnance is indeed detected because mine detectors have error. Therefore, we also consider probabilistic methods to determine paths for the robot to maximize the likelihood of detecting all ordnance in a target location using a priori known information.