bluuebunny/crossref_metadata_2025 huggingface dataset:
An Instrumented Medical Hammer With Diagnostic, Therapeutic and Pedagogical Applications
Authors: Meinhold Waiman , Kaplan Evan , Ueda Jun , Mori Takayuki , Izumi Shin-ichi
Published: November 2017

Medical hammers are a commonly used medical device with both diagnostic and therapeutic uses. Tendon tapping to elicit the T-Reflex is a widely used medical procedure that serves as a high level diagnostic tool for many neurological disorders. Previous work has also suggested the utility of the technique for therapeutic purposes. This work discusses the development and initial testing of an instrumented networked medical hammer. An accompanying scheme for wireless data collection and real-time clinical feedback is proposed and partially implemented. The work represents an important improvement to previous efforts in quantification of tendon reflex responses. Not only is intensity of the full impact measured, a method for determining the location of hammer impact is also presented. Stimulus location classification is done via Support Vector Machine (SVM). Variability between and within clinician tapping methods is confirmed, along with validation of SVM for differentiating between clinicians. The automated determination of impact location provides a foundation for work in both rehabilitation and clinical diagnostics.
A Sum-of-Squares Polynomial Approach for Road Anomaly Detection Using Vehicle Sensor Measurements
Authors: Shu Dule , Lagoa Constantino , Cleary Timothy
Published: November 2017

This paper presents a new method for road anomaly detection. The existence of road anomalies is determined by the behaviors of vehicles. A special polynomial named Sum-of-Squares (SOS) polynomial is used as a metric to evaluate the normality of vehicle behaviors. The method can process multiple types of sensor measurements. A feature extraction method is used to obtain concise representations of the sensor measurements. These representations, called feature points, are used to calculate the value of the SOS polynomial. Simulation results have been shown to demonstrate that the proposed method can effectively detect different types of road anomalies.
Distributed MPC via ADMM for Coordination and Control of More Electric Aircraft Subsystems
Authors: Dunham William , Hencey Brandon , Girard Anouck , Kolmanovsky Ilya
Published: November 2017

A distributed model predictive controller is developed for the coordination of subsystems in a more electric aircraft, and its performance is compared with the centralized MPC approach. The distributed MPC solution is based on the alternating direction method of multipliers, that allows local subsystem controllers to converge to a system wide optimal solution while enforcing local state and control constraints. Based on simulations, we demonstrate that this distributed approach to coordination of electrical power and engine subsystems has the potential to achieve comparable performance to the centralized solution.
Air-Fuel Ratio Control of Lean-Burn SI Engines Using Fuzzy Sliding-Model Technique
Authors: Wu Hsiu-Ming , Tafreshi Reza
Published: November 2017

Minimization of the carbon dioxide and harmful pollutants emissions and maximization of fuel economy for the lean-burn spark ignition (SI) engines significantly rely on precise air-fuel ratio (AFR) control. However, the main challenge of AFR control is the large time-varying delay which exists in lean-burn engines. Since the system is usually subject to external disturbances and uncertainties, a high level of robustness in the AFR control design has to be considered. Herein, a fuzzy sliding-mode control (FSMC) technique is proposed to track the desired AFR in the presence of periodic disturbances. The proposed method is model free and does not need any system characteristics. Based on the fuzzy system input-output data, two scaling factors are first employed to normalize the sliding surface and its derivative. According to the concept of the if-then rule, an appropriate rule table for the logic system is designed. Finally, the feasibility and effectiveness of the proposed control scheme are evaluated under various operating conditions.
Symmetric Control Design for Multi-Evaporator Vapor Compression Systems
Authors: Danielson Claus
Published: November 2017

Multi-evaporator vapor compression systems (ME-VCS) are inherently multi-input multi-output (MIMO) systems, often with complex, highly coupled dynamics. Thus, they require more sophisticated control schemes than traditional on-off logic, or decentralized proportional-integral controllers. Unfortunately, many MIMO control design techniques are not well suited for this problem since they require complex numerical computations that do not scale gracefully for the high-dimensional dynamics of ME-VCS systems. This paper exploits the observed similarity of the room dynamics to reduce the computational complexity of designing controllers. We use a linear matrix inequality based controller synthesis technique that exploits symmetry for designing controllers for large-scale ME-VCS systems. This controller synthesis technique was applied to an ME-VCS system with 50 rooms. Using tradition control design methods required 41 hours to synthesize a controller, while our technique designed an identical controller in less than 1 second.
Geometric Control of Quadrotor Attitude in Wind With Flow Sensing and Thrust Constraints
Authors: Craig William , Paley Derek A.
Published: November 2017

Quadrotor vehicles show great potential over a range of tasks, but effective control in windy environments continues to be a challenge. This paper develops a thrust-saturated controller on the Lie group SO (3) that uses flow sensing in order to reduce the effect of gusts on the vehicle. Designing the controller on SO (3) establishes almost-global exponential stability, and avoids the pitfalls of representing rigid-body kinematics using Euler angles. We prove that exponential stability is retained in the presence of thrust saturation. Aerodynamics are incorporated into the dynamics and control through a model of the blade-flapping phenomena experienced by rotorcraft. Numerical examples show that the system control remains effective despite thrust saturation, and that flow sensing improves both the initial response and steady-state error of the system in wind.
Robustness Analysis for Simultaneous Resource Allocation and Route Optimization Problems
Authors: Srivastava Amber , Salapaka Srinivasa M.
Published: November 2017

This paper presents the robustness analysis for an algorithm that solves simultaneous resource allocation and route optimization problem (SARO). These problems appear in the context of multi-hop routing applications in sensor networks, which require placement of multiple resource nodes and determining routes from each sensor location to a common data destination center via these resource nodes. In [1], we proposed an algorithm based on Maximum Entropy Principle that addressed the determination of locations of these resource nodes and the corresponding multi-hop routing problem such that the total communication cost is minimized. Such placement of resource nodes is sensitive to multiple parameters such as sensor locations, destination center location, communication costs between sensor and resource nodes, between resource nodes, and between resource nodes and destination center. This paper studies the sensitivity of the solution from the algorithm to these parameters. This robustness analysis is necessary since some of these parameters are typically not known precisely, the sensitivity analysis helps the network design by identifying the hierarchy in parameters in terms of how they affect the algorithm solution, and therefore also indicate how precisely these parameters need to be estimated. In this direction, we propose a modification of our algorithm to account for the uncertainty in sensor locations; here a probability distribution of sensor locations instead of their precise locations is assumed to be known. We also present and characterize a phase-transition aspect of the algorithm, where the number of distinct locations of resource nodes increase at certain critical values of annealing variable — a parameter in the algorithm. Simulations are provided that corroborate our analysis and instantiate relative sensitivities between different parameters.
Coordinated and Semi-Adaptive Cardiorespiratory Control via Sedative and Opioid Drugs
Authors: Jin Xin , Kim Chang-Sei , Shipley Steven T. , Dumont Guy A. , Hahn Jin-Oh
Published: November 2017

This paper presents a coordinated semi-adaptive approach to closed-loop control of cardiorespiratory state in critically ill patients through the infusion of sedative and opioid drugs. The proposed approach is built upon an upper level multiple drug coordination loop and a lower level semi-adaptive control loop. The coordination loop recursively adjusts the target set points based on the dose-response relationship of a patient estimated by the semi-adaptive control loop, so as to ensure that the target set points become achievable. The semi-adaptive control loop drives the patient state to the target set points while estimating the patient’s dose-response relationship. Hence, the proposed control approach can adjust target set points erroneously specified by caregivers while respond effectively to the need of individual patients. To realize the proposed control approach, we developed (1) a two-input two-output dose-response model of interacting sedative and opioid drugs; (2) a semi-adaptive control algorithm to drive patient state to target set points while selectively estimating high-sensitivity parameters in the dose-response model; and (3) a multiple drug coordination algorithm that reconciles caregiver preference and individual patient’s drug needs. The proposed control approach was evaluated in an example cardiorespiratory control scenario in which cardiac output and respiratory rate are regulated via the infusion of propofol and remifentanil in an in-silico simulation setting. The results show that the coordinated semi-adaptive control could (1) track achievable target set point with robust transient and steady-state error performance and (2) adjust the unachievable target set points to achievable ones.
Boundary Value Problem Method to Investigate Superharmonic Resonance of MEMS Resonators
Authors: Beatriz Julio , Botello Martin , Reyes Christian , Caruntu Dumitru I.
Published: November 2017

This paper deals with two different methods to analyze the amplitude frequency response of an electrostatically actuated micro resonator. The methods used in this paper are the method of multiple scales, which is an analytical method with one mode of vibration. The other method is based on system of odes which is derived using the partial differential equation of motion, as well as the boundary conditions. This system is then solved using a built in matlab function known as BVP4C. Results are then shown comparing the two methods, under a variety of parameters, including the influence of damping, voltage, and fringe.
Traffic Sign Recognition in Autonomous Vehicles Using Edge Detection
Authors: Vishwanathan Harish , Peters Diane L. , Zhang James Z.
Published: November 2017

Autonomous vehicles have the potential to improve safety by eliminating human error in driving, as well as providing mobility to those who cannot safely drive. Such vehicles do require new technology to monitor their environment and ensure that they are operating safely. One such technology that will be necessary is the ability of the vehicle to recognize traffic situations and traffic signs. This can be accomplished by an appropriate implementation of edge detection methods. In this paper, we compare three different edge detection methods: Canny method, Sobel method and Zhang method. This comparison was conducted on both still pictures and on a video. When analyzing the video, which was taken on a clear day with an undamaged and clearly visible stop sign, all three methods performed equally well; the time at which the stop sign was identified, based on the edge map, was the same. The purpose of this comparison is to evaluate the performance of each of the three methods, in the context of the problem of identifying traffic signs. The methods are compared on still images of a stop sign under various conditions, in addition to the single video comparison. Based on the still image comparison, we conclude that Zhang’s method (linear prediction) generates the best edge map, particularly when the images include snow, ice, rain or other factors and even at night vision.
Controlling Physical Interactions: Humans Do Not Minimize Muscle Effort
Authors: Koeppen Ryan , Huber Meghan E. , Sternad Dagmar , Hogan Neville
Published: November 2017

Physical interaction with tools is ubiquitous in functional activities of daily living. While tool use is considered a hallmark of human behavior, how humans control such physical interactions is still poorly understood. When humans perform a motor task, it is commonly suggested that the central nervous system coordinates the musculo-skeletal system to minimize muscle effort. In this paper, we tested if this notion holds true for motor tasks that involve physical interaction. Specifically, we investigated whether humans minimize muscle forces to control physical interaction with a circular kinematic constraint.

Using a simplified arm model, we derived three predictions for how humans should behave if they were minimizing muscular effort to perform the task. First, we predicted that subjects would exert workless, radial forces on the constraint. Second, we predicted that the muscles would be deactivated when they could not contribute to work. Third, we predicted that when moving very slowly along the constraint, the pattern of muscle activity would not differ between clockwise (CW) and counterclockwise (CCW) motions.

To test these predictions, we instructed human subjects to move a robot handle around a virtual, circular constraint at a constant tangential velocity. To reduce the effect of forces that might arise from incomplete compensation of neuro-musculo-skeletal dynamics, the target tangential speed was set to an extremely slow pace (∼1 revolution every 13.3 seconds). Ultimately, the results of human experiment did not support the predictions derived from our model of minimizing muscular effort. While subjects did exert workless forces, they did not deactivate muscles as predicted. Furthermore, muscle activation patterns differed between CW and CCW motions about the constraint. These findings demonstrate that minimizing muscle effort is not a significant factor in human performance of this constrained-motion task. Instead, the central nervous system likely prioritizes reducing other costs, such as computational effort, over muscle effort to control physical interactions.
Crane Lift-Off Control of Inclined Payloads
Authors: Toth Michael J. , Lewallen Colby F. , Hanson Joseph C. , Wang Shenghai , Singhose William
Published: November 2017

It is difficult for crane operators to lift and maneuver payloads without causing significant, uncontrolled motion. Consequently, research in the area of crane operation has focused on designing controllers to minimize payload swing. However, lifting long and slender payloads (e.g., steel I-beams) from a non-level surface (e.g., like many outdoor construction sites) has not been addressed in much detail. This paper evaluates the amplitude of residual swing and robustness of two different control methodologies while hoisting a slender payload up into the air from an inclined surface. A semi-automatic approach, where the crane operator controls the lift direction and a proportional-integral-derivative (PID) controller adjusts the overhead trolley position, was developed. Experimental tests demonstrate that this method reduces the peak amplitude of residual vibration by about 80% for most non-zero incline angles.
Uncertainty and Disturbance Estimation for Quadrotor Control Using Extended High-Gain Observers: Experimental Implementation
Authors: Boss Connor J. , Lee Joonho , Choi Jongeun
Published: November 2017

This paper presents a complete experimental implementation of an Extended High-Gain Observer (EHGO) based disturbance and uncertainty estimator for use in quadrotor control. The system is designed as a multi-time-scale system to deal with mechanical underactuation and to ensure convergence of EHGO estimates for use in the output feedback control. The lumped, estimated disturbance is passed into the rotational dynamic inversion based control, and the feedback linearization based translational control to cancel the estimated disturbances. This results in a feedback control scheme that is robust to external disturbances as well as model uncertainties, such as an uncertain air-frame mass and rotational inertial matrix. The control is verified through simulation and experimental results.
A Finite State Machine Based Automated Driving Controller and its Stochastic Optimization
Authors: Zhang Mengxuan , Li Nan , Girard Anouck , Kolmanovsky Ilya
Published: November 2017

In this paper, we develop a finite state machine based automated highway driving controller. The controller is described by feedback control laws in each state and state transition conditions. We test the controller in a traffic simulator and evaluate its performance based on a metric function. Furthermore, we propose a stochastic gradient based optimization approach to achieve optimal calibration of the developed controller. We expect that this controller can serve as a baseline for automated driving algorithm developments.
Modeling and Adaptive Nonlinear Disturbance Observer for Closed-Loop Control of In-Ground-Effects on Multi-Rotor UAVs
Authors: He Xiang , Calaf Marc , Leang Kam K.
Published: November 2017

This paper focuses on modeling and nonlinear control of in-ground-effect (IGE) on multi-rotor aerial vehicles such as quadrotor helicopters (quadcopters). As the vehicle flies and hovers near obstacles such as the ground, walls, and other features, the IGE which is a function of the distance between the rotor and the obstacle induces a thrust that drastically affects flight behavior. This effect on each rotor can be vastly different as the vehicle’s attitude varies. Furthermore, IGE limits the ability for precision flight control, navigation, and landing in tight and confined spaces. A nonlinear model is proposed to predict the IGE for each rotor. To compensate for the IGE, an adaptive nonlinear disturbance observer (ANDO) is designed to enhance closed-loop PID control. The observer and controller are implemented in a simulation framework, where results show significant improvement in performance compared to the case without observing and compensating for the IGE. In particular, it is shown that the ANDO PID closed-loop controller improves the settling time by approximately 60%.
Vehicle Stabilization During Critical Cornering Scenarios Using Sliding Surface Control
Authors: Boyd Christina , Beal Craig E.
Published: November 2017

Crash statistics demonstrate that speeding is often associated with loss of control vehicle crashes. This paper presents an approach which integrates steering and braking actuation to provide driver support in corner over-speed scenarios. The proposed hierarchical controller defines a path-following function for the desired cornering radius and then determines appropriate braking and steering inputs, using sliding surface control, to drive the vehicle to the desired path. Simulations demonstrate that the sliding surface controller design can outperform a human driver model in keeping the vehicle on the roadway, employing a complex sequence of braking and steering inputs only feasible with the addition of a modern vehicle control system.
Robustness and Adaptability Analysis of Future Military Modular Fleet Operation System
Authors: Li Xingyu , Epureanu Bogdan I.
Published: November 2017

Modular vehicles are vehicles with interchangeable substantial components also known as modules. Fleet modularity provides a system with extra operational flexibility through on-field actions, in terms of vehicle assembly, disassembly, and reconfiguration. The ease of assembly and disassembly of modular vehicles enables them to achieve real-time fleet reconfiguration in order to reach time-changing combat environments and constantly update their techniques. Previous research reveals that life cycle costs, especially acquisition costs, shrink significantly as a result of fleet modularization. In addition, military field demands and enemy attacks are highly unpredictable and uncertain. Hence, it is of interest to the US Army to investigate the robustness and adaptability of a modular fleet operation system against demand uncertainty. We model the fleet operation management in a stochastic state space model while considering time delays from operational actions, as well as use model predictive control (MPC) to attain real-time optimal operation actions based on the received demands and predicted system status.

Analyses on the robustness and adaptability of how a modular vehicle fleet reacts to the demand disturbance and noise have been very limited, although research on operation management and model prediction control have been ongoing for many years. In our current study, we model all the main processes in a fleets operation into an integrated system. These processes include module resupply, vehicle transportation, and on-base assembly, disassembly, reconfiguration (ADR) actions. We also consider the fact that delayed field demands trigger additional demands, which might cause system instability under improper operational strategies. We have designed a predictive control approach that includes an optimizer and a simulation process to monitor and control the fleet operation. Under the identical mission demands and fleet configuration settings, a modular vehicle fleet shows a faster reaction speed than a conventional fleet once demand disturbance and noise are injected. Although our study is inspired by a military application, it is not hard to notice that our system also represents a simplified supply chain structure. Thus, our methodology can also be generalized for civilian applications.
Design and Fabrication of Desktop Fiber Manufacturing Kit for Education
Authors: Kim David Donghyun , Anthony Brian
Published: November 2017

Fiber manufacturing process has been an integral part of the optical fiber communications. The optical fiber manufacturing processes involve high precision quality control and large volume production. However, the conventional fiber drawing manufacturing technologies are not flexible and highly specialized. This prevents innovative ideas such as flexible fiber manufacturing and small scale prototypes. A desktop fiber manufacturing kit was designed and tested. The experimental results indicate that diameter can be controlled within 0.02mm with standard deviation of 0.120mm when target diameter was set to be 0.5mm. Proportional control can be used to adjust fiber diameters.
Robot Swarm for Efficient Area Coverage Inspired by Ant Foraging: The Case of Adaptive Switching Between Brownian Motion and Lévy Flight
Authors: Deshpande Aditya , Kumar Manish , Ramakrishnan Subramanian
Published: November 2017

Design of robot swarms inspired by self-organization in social insect groups is currently an active research area with a diverse portfolio of potential applications. In this work, the authors propose a control law for efficient area coverage by a robot swarm in a 2D spatial domain, inspired by the unique dynamical characteristics of ant foraging. The novel idea pursued in the effort is that dynamic, adaptive switching between Brownian motion and Lévy flight in the stochastic component of the search increases the efficiency of the search. Influence of different pheromone (the virtual chemotactic agent that drives the foraging) threshold values for switching between Lévy flights and Brownian motion is studied using two performance metrics — area coverage and visit entropy. The results highlight the advantages of the switching strategy for the control framework, particularly in cases when the object of the search is scarce in quantity or getting depleted in real-time.
Iterative In-Situ 3D Layout Optimization of a Reconfigurable Ocean Current Turbine Array Using Bayesian Optimization
Authors: Baheri Ali , Ramaprabhu Praveen , Vermillion Christopher
Published: November 2017

In this paper, we present an online approach for optimizing the 3D layout of an ocean current turbine (OCT) array. Unlike towered turbines, most OCT concepts for Gulf Stream energy harvesting involve tethered systems. The replacement of towers with tethers provides the opportunity for OCTs to adjust their locations within some domain by paying out/in tether to adjust depth and manipulating control surfaces (elevators and rudders) to adjust longitudinal and lateral positions. The ability to adjust the OCT positions online provides the capacity to reconfigure the array layout in response to changing flow conditions; however, successful online array layout reconfiguration requires optimization schemes that are not only effective but also enable fast convergence to the optimal configuration. To address the above needs, we present a reconfigurable layout optimization algorithm with two novel features. First, we describe the location of each turbine through a small set of basis parameters; the number of basis parameters does not grow with increasing array size, thereby leading to an optimization that is not only computationally tractable but is also highly scalable. Secondly, we use Bayesian Optimization to optimize these basis parameters. Bayesian Optimization is a very powerful iterative optimization technique that, at every iteration, fuses a best-guess model of a complex function (array power as a function of basis parameters, in our case) with a characterization of the model uncertainty in order to determine the next evaluation point. Using a low-order analytical wake interaction model, we demonstrate the effectiveness of the proposed optimization approach for various array sizes.
A Graph-Based Approach for Dynamic Compressor Modeling in Vapor Compression Systems
Authors: Aksland Christopher T. , Koeln Justin P. , Alleyne Andrew G.
Published: November 2017

Vapor compression systems are widely used as thermal management systems. To satisfy thermal demands, models are used to control and optimize the system’s performance, reliability, and efficiency. Significant effort has been made to model the condenser and evaporator, while there has been minimal focus on control-oriented modeling of the compressor. Initial work illustrates that during transient behavior, the working fluid exhibits a fast dynamic. However, during a startup and shutdown sequence, the working fluid follows a slower dynamic believed to be associated with heat transfer to the shell. To address both thermal dynamics, a graph-based modeling approach is used to incorporate the compressor shell’s thermal capacitance into the model. Experimental and simulation data are compared for a range of operating conditions including shutdown and startup dynamics.
Design and Hybrid Impedance Control of a Powered Rowing Machine
Authors: de las Casas Humberto , Richter Hanz , van den Bogert Antonie
Published: November 2017

A conventional rowing machine was modified with an electric motor and a robust impedance control system to mimic the behavior of a conventional rower and subsequently expand its versatility. The powered machine has programmable impedance and can produce controlled forces during the return stroke, allowing for eccentric exercise. Conventional rowers do not allow eccentric loading, an exercise modality known to contribute significantly to the efficacy of training. Eccentric loading is particularly important to diminish the detrimental effects of humans operating in microgravity for long periods of time. Conventional rowers include a flywheel, a fan and a freewheeling clutch. These elements were removed and replaced by a torque-controlled motor and a belt transmission selected on the basis of the forces and velocities encountered in the rowing exercise. A hybrid dynamic model was developed for the conventional rowing machine to account for its force-velocity characteristics and the transitions between the coupled (pull stroke) and the decoupled (return stroke) of the freewheeling clutch. Machine parameters such as flywheel inertia, air damping coefficients and return spring constants were identified from a set of experimental data and fitted to the model. The model was then used to design the robust hybrid impedance controller which includes a virtual flywheel and a force sensor to determine the transitions between pull and return strokes. The controller reproduces the operation of the original machine and can also be programmed to produce arbitrary impedances. The paper describes the hybrid dynamic model and control approach and the real-time experimental trials.
Reduction of Transient Payload Swing in a Harmonically Excited Boom Crane by Shaping Luff Commands
Authors: Newman Daniel , Vaughan Joshua
Published: November 2017

The control of boom cranes is a topic that has generated a significant amount of research. Particularly, cranes mounted on ocean-going ships pose a significant challenge. Due to the harmonic disturbance resulting from ocean conditions, open-loop control methods such as input shaping have been largely ignored in this area of research. This work will develop linearized governing equations for a planar, harmonically-excited boom crane. Using these approximations, a command-shaping strategy that minimizes payload deflection during and shortly after a luff command will be presented. It is anticipated that this method will be used to smooth the transition to a closed-loop controller which engages after the operator-given command is complete.
Optimal Control and Switching Mechanism of a Power Station With Identical Generators
Authors: Yao Fulai , Gao Qingbin
Published: November 2017

This paper proposes a novel approach for optimizing the total power output of a generalized power station with identical generators by analyzing the characteristics of the efficiency function. The introduced treatment yields the maximum total power supply and the maximum overall efficiency for the generalized power station. To achieve these, the input factor for each generator is kept the same, and the optimal switch points are selected to be the same efficiency points of two operating methods.
Sign Inverting Control and its Important Properties for Multiple Time-Delayed Systems
Authors: Gao Qingbin , Zhang Zhenyu , Yang Chifu
Published: November 2017

This paper provides new results for a newly introduced control scheme, Sign Inverting Control (SIC), for linear time-invariant multiple time delay systems (LTI-MTDS). SIC suggests the inversion of the control polarity for delayed systems and it functions with one single requirement that the union of the control schemes provides a larger operating region in the domain of the delays than each of its components does. To meet this need, we propose a new method to characterize the potential stability-switching hypersurfaces for SIC applied systems. The acquisition of these hypersurfaces is a prerequisite for the description of the overall stability map. The new results in this paper reveal the relationship between the hypersurfaces of the SIC applied system and the original nominal system. As a result, the procurement of the hypersurfaces and stability map of the SIC applied system has been facilitated. Several illustrative example case studies are presented.
Comparative Study of Rack Force Estimation for Electric Power Assist Steering System
Authors: Li Yijun , Shim Taehyun , Wang Dexin , Offerle Timothy
Published: November 2017

For an electric power assist steering (EPAS) control system, it is important to know the rack force information to improve the steering feel control performance. Since there is no direct measurement of rack force in current EPAS system, there have been various rack force estimation algorithms proposed for the control system development. In this paper, two existing rack force estimation methods (based on steering system dynamics and vehicle dynamics) have been implemented in the simulation environment to compare its performance. The effectiveness and limitations of two methods have been analyzed using a simulation of high fidelity EPAS model with various inputs conditions. In addition, new adaptation algorithm is proposed to further improve the estimation performance of the existing methods.
Trajectory Generation for a Lower Limb Exoskeleton for Sit-to-Stand Transition Using a Genetic Algorithm
Authors: Chamnikar Ameya S. , Patil Gaurav , Radmanesh Mohammadreza , Kumar Manish
Published: November 2017

Population of the world above the age of 65 years is increasing rapidly. Aging causes weakening of human joints which increases constraints on mobility of the body. Sit-to-Stand (STS), an important part of Activities of Daily Living (ADL) is one of the motions that is affected because of weakened joints. With the lack of personal care there is going to be a need for devices which can assist the aging population in STS. We propose the use of a lower-limb exoskeleton as an assistive device. One of the main challenges in this area is to generate a human like reference trajectory for exoskeleton to follow. This paper proposes the use of Genetic Algorithm (GA), to generate reference trajectories for the joint angles for lower limb exoskeleton for STS transition. The fitness function for the GA presented here is constructed based on the fact that for a successful STS center of mass (COM) needs to stay in the area of support. After the trajectory generation a simple controller is proposed to control a 3 degrees of freedom exoskeleton. The dynamics of the system being controlled are modelled as an inverse 3 degrees of freedom pendulum and the equations are derived using the Euler-Lagrange equation. The highly non-linear dynamics are linearized using an input-output feedback linearization technique. A PD controller is presented for this linearized dynamic system and the validation of the controller is done using simulations. Simulation results show that GA successfully generates a human like trajectory which eliminates the need to use motion tracking system for measuring human trajectories.
Real-Time Optimization of Wind Farm Energy Capture With Delay Compensated Nested-Loop Extremum Seeking Control
Authors: Wu Zhongyou , Li Yaoyu
Published: November 2017

Real-time optimization of wind farm energy capture for below rated wind speed is critical for reducing the levelized cost of energy (LCOE). Performance of model based control and optimization techniques can be significantly limited by the difficulty in obtaining accurate turbine and farm models in field operation, as well as the prohibitive cost for accurate wind measurements. The Nested-Loop Extremum Seeking Control (NLESC), recently proposed as a model free method has demonstrated its great potential in wind farm energy capture optimization. However, a major limitation of previous work is the slow convergence, for which a primary cause is the low dither frequencies used by upwind turbines, primarily due to wake propagation delay through the turbine array. In this study, NLESC is enhanced with the predictor based delay compensation proposed by Oliveira and Krstic [1], which allows the use of higher dither frequencies for upwind turbines. The convergence speed can thus be improved, increasing the energy capture consequently. Simulation study is performed for a cascaded three-turbine array using the SimWindFarm platform. Simulation results show the improved energy capture of the wind turbine array under smooth and turbulent wind conditions, even up to 10% turbulence intensity. The impact of the proposed optimization methods on the fatigue loads of wind turbine structures is also evaluated.
Design of a Passive Exoskeleton Knee to Assist Toe Clearance
Authors: Wu Shang-Li , Kazerooni Homayoon
Published: November 2017

This paper presents a fully passive exoskeleton knee that resists knee buckling during the stance phase, encourages knee flexion to assist in toe clearance during the swing flexion phase, and allows free swing extension. This knee device utilizes a spring to store and release energy in different phases. It realizes a complex implementation with a simple architecture by using a four-bar linkage mechanism with the knowledge of the mechanism with variable topologies (MVTs). In this article, a fully passive knee prototype was designed, optimized, and built. The knee device is hypothesized to enable walking and assist toe clearance in exoskeleton walking. This article opens a paradigm of the passive knee devices that tackles the problem of low toe clearance, not only for implementation of the exoskeletons but also for orthoses and prostheses.
Development of a Mechatronics Course Integrated With Lab
Authors: Samanta Biswanath
Published: November 2017

This paper reports the development of an introductory mechatronics course in Mechanical Engineering (ME) undergraduate program at Georgia Southern University. This an updated version of an existing required course in the ABET accredited BSME program. The course covers three broad areas: mechatronic instrumentation, computer based data acquisition and analysis, and microcontroller programming and interfacing. This is a required 3-credit course in the ME program with updated computing application specific content reinforcing theoretical foundation with hands-on learning activities of the existing course. The course has four contact hours per week with two hours of lecture and two hours of interactive session of problem solving and laboratory experiment. For each topic covered, students get the theoretical background and the hands-on experience in the laboratory setting. Both formative and summative assessment of the students’ performance in the course are planned. Both direct and indirect forms of assessment are considered. The paper reports the details of the course materials.
Customer Usage Based on Pseudo Damage
Authors: Altmann Craig T. , Ferris John B.
Published: November 2017

Modeling customer usage in vehicle applications is critical in performing durability simulations and analysis in early design stages. Currently, customer usage is typically based on road roughness (some measure of accumulated suspension travel), but vehicle damage does not vary linearly with the road roughness. Presently, a method for calculating a pseudo damage measure is developed based on the roughness of the road profile, specifically the International Roughness Index (IRI). The IRI and pseudo damage are combined to create a new measure referred to as the road roughness-insensitive pseudo damage. The road roughness-insensitive pseudo damage measure is tested using a weighted distribution of IRI values corresponding to the principal arterial (highways and freeways) road type from the Federal Highway Administration (FHWA) Highway Performance Monitoring System (HPMS) dataset. The weighted IRI distribution is determined using the number of unique IRI occurrences in the functional road type dataset and the Average Annual Daily Traffic (AADT) provided in the FHWA HPMS data.
Modeling and Characterization of Driving Styles for Adaptive Cruise Control in Personalized Autonomous Vehicles
Authors: Bolduc Drew , Guo Longxiang , Jia Yunyi
Published: November 2017

For autonomous vehicles to gain widespread customer acceptance, safety and reliability are not nearly enough. Comfort and familiarity of the ride is also of essential importance. Because these are highly subjective factors, autonomous vehicles must be able to adopt personal driving styles to meet individual preference. The adaptive cruise control (ACC) system is a critical function performed by the autonomous vehicle and much research effort has been devoted to the development of a system that acts as a human driver. However, studies which investigate ACC models capable of learning a driving style are limited. In this paper, we propose a method to extract quantifiable parameters which represent a drivers’ driving style and apply these parameters to personalize the longitudinal control of an autonomous vehicle. We then develop a longitudinal driver model that integrates those parameters to enable the ACC system to mimic the driving style of the driver. Finally, the effectiveness of the extraction method and the driver model are obtained through simulation.
State Estimation of an Advanced Rowing Machine Using Optimized Kalman Filtering
Authors: Mohammadi Hanieh , Khademi Gholamreza , Simon Dan , Richter Hanz
Published: November 2017

This research addresses the problem of state estimation of an advanced rowing machine with energy regeneration. It is assumed that the states of the system, which are position, velocity, and capacitor charge, are measurable. The user force input to the system can be measured by load cells. It is shown that the need for load cells can be eliminated by estimating the force with an unknown-input Kalman filter. The estimated states and the unknown user force input are passed to the controller of the system, which is either an inversion-based controller or a semi-active impedance controller. Two friction models are considered for this system: Coulomb friction, and LuGre friction. The Kalman gains are tuned using an evolutionary algorithm to minimize the standard deviation of the estimation error. The results verify the effectiveness of the proposed approach for simultaneous estimation of the states and the input force. The standard deviation of the state estimation errors are only 10% of their measurement noise. The standard deviation of the input force estimation error is 0.1 N when using an optimized Kalman gain, which is only 25% of the value obtained when using manually tuned gains.
Obstacle Identification for Vision Assisted Control Architecture of a Hybrid Mechanism Mobile Robot
Authors: Kumar Anil , Ren Hailin , Ben-Tzvi Pinhas
Published: November 2017

This paper presents a monocular vision-based, unsupervised floor detection algorithm for semi-autonomous control of a Hybrid Mechanism Mobile Robot (HMMR). The paper primarily focuses on combining monocular vision cues with inertial sensing and ultrasonic ranging for on-line obstacle identification and path planning in the event of limited wireless connectivity. A novel, unsupervised vision algorithm was developed for floor detection and identifying traversable areas, in order to avoid obstacles in semi-autonomous control architecture. The floor detection algorithms were validated and experimentally tested in an indoor environment under various lighting conditions.
A Novel Low Voltage Electrostatic MEMS Resonator Sensor Based on Double Resonance Dynamic Amplification
Authors: Alsaleem Fadi M. , Hasan Mohammad H.
Published: November 2017

In this paper, we present a new concept to couple the mechanical vibration dynamic of electrostatic MEMS sensor with its internal electrical circuit resonance. The concept shows great potential to reduce the excitation voltage for electrostatic MEMS. The proposed actuation method aims to activate the mechanical and electrical resonance of the MEMS circuit, simultaneously; to amplify the voltage across the MEMS and increase the MEMS sensitivity to the input electrostatic forces. Moreover, we propose a method to achieve this amplification for any electrostatic MEMS device regardless of the values of its electrical and mechanical resonance frequencies. The proposed concept is studied theoretically and validated experimentally for a commercial MEMS sensor. A voltage amplification of more than 21 times and a MEMS amplitude amplification of over 6 times was observed.
Proxy-Based Optimal Dynamic Control Allocation for Multi-Input, Multi-Output Over-Actuated Systems
Authors: Duan Molong , Okwudire Chinedum
Published: November 2017

In over-actuated systems, an output can be realized through various control effort combinations. It is desirable to allocate the control efforts dynamically (as opposed to statically) in an optimal manner. In this paper, a proxy-based control allocation approach is proposed for multi-input, multi-output over-actuated systems. Instead of using real-time optimization for control allocation, the proposed method establishes an energy optimal subspace; it then defines a causally implementable proxy to accurately measure the deviation of the controlled system from the energy optimal subspace using matrix fraction description and spectral factorization. The control allocation problem is thus converted to a regulation problem, and is solved using a standard H∞ approach. The proposed method is validated through simulation examples, in comparison with an existing dynamic control allocation method. Significant improvements in energy efficiency without affecting the controlled output are demonstrated.
Extended Kalman Filter-Aided Active Beam Tracking for LED Communication in 3D Space
Authors: Solanki Pratap Bhanu , Tan Xiaobo
Published: November 2017

Maintaining Line-Of-Sight (LOS) between the receiver and the transmitter is an inherent challenge associated with light-emitting diode (LED)-based free space optical communication systems, especially when such systems are used by mobile robots. Due to constant movement of underlying robotic platforms and other unwanted disturbances, there is a need for an active alignment system that allows the receiver to constantly track the direction of the transmitting device. In this paper, we propose an active alignment control system, equipped with two degree-of-freedom (DOF) actuation and capable of tracking a transmitting source moving in the three-dimensional (3D) space. A 3D extension of a previously proposed Extended Kalman Filter-based algorithm is used to estimate the components of the angle between the receiver orientation and the receiver-transmitter line, which are used subsequently to adjust the receiver orientation. The algorithm uses only the measured light intensity from a single photo-diode, where successive measurements are obtained via a circular scanning technique. Simulation results are presented to illustrate the proposed approach and explore the tradeoffs in the design of the scanning pattern. In particular, a scheme with adaptively adjusted scanning amplitude is shown to deliver satisfactory alignment performance with actuation effort.
Simulation Based Design of a Thermoelectric Energy Harvesting Device for Aircraft Applications
Authors: Lyras Michalis , Zymaride Lito , Kyratsi Theodora , Louca Loucas S. , Becker Thomas
Published: November 2017

Maintenance is, amongst others, a key cost driver in aircraft operation. A wireless monitoring device might be able to reduce these costs. However, the supply of energy to such system via power lines would result in additional cabling and battery operation would lead to additional maintenance. Thermoelectric energy harvesting, as a power source for such devices, is considered as one the most promising approaches for autonomous energy conversion onboard fixed wing aircraft. Using thermoelectric generators (TEGs), the temperature difference, between the inside and outside of the cabin, can be used to generate electrical energy.

In this paper an energy harvesting device, for aircraft application needs and requirements, is designed and optimized using modeling and simulation. A variety of models are used for analyzing the static and dynamic behavior of the device. A one-dimensional heat transfer model is used to identify critical parameters, while a detailed three-dimensional heat-transfer and airflow model is used to study realistic operating conditions. The proposed design leads to a significant increase of peak and average output power, specific energy productions and decrease of response time of the harvester.