bluuebunny/crossref_metadata_2025 huggingface dataset:
Human-Inspired Algebraic Curves for Wearable Robot Control
Authors: Mohammadi Alireza , Gregg Robert D.
Published: November 2018

Having unified representations of human walking gait data is of paramount importance for wearable robot control. In the rehabilitation robotics literature, control approaches that unify the gait cycle of wearable robots are more appealing than the conventional approaches that rely on dividing the gait cycle into several periods, each with their own distinct controllers. In this article we propose employing algebraic curves to represent human walking data for wearable robot controller design. In order to generate algebraic curves from human walking data, we employ the 3L fitting algorithm, a tool developed in the pattern recognition literature for fitting implicit polynomial curves to given datasets. For an impedance model of the knee joint motion driven by the hip angle signal, we provide conditions by which the generated algebraic curves satisfy a robust relative degree condition throughout the entire walking gait cycle. The robust relative degree property makes the algebraic curve representation of walking gaits amenable to various nonlinear output tracking controller design techniques.
Model Predictive Air-Fuel Ratio Control for an Integrated Gasoline Engine and Three-Way Catalytic Converter System
Authors: Yang Kuo , Chen Pingen
Published: November 2018

With increasingly demanding regulations on engine emission and fuel efficiency, the optimization of the internal combustion engine and the after-treatment integrated system has become a critical research focus. To address such an issue, this paper aims to achieve a better trade-off between the fuel consumption of a spark-ignited (SI) engine and emission conversion efficiencies of a Three-Way Catalytic converter (TWC) system. A Model Predictive Control (MPC)-based integrated engine and TWC control methodology is presented, which is able to optimize Air/Fuel Ratio (AFR) to maintain oxygen storage of TWC at a desired level and thus meet the tailpipe NOx, CO and HC emission requirements. The effectiveness of the presented control methodology is validated in simulation. Compared with the existing dithering-based AFR control, the proposed MPC-based AFR control can improve CO emission conversion efficiencies by 8.42% and 4.85% in simplified US06 and UDDS driving cycles, respectively. At the same time, Nitrogen Oxides (NOx) conversion efficiency maintains above the required limit of 95% and the fuel efficiency remains at the same level as the existing control methodology in production as well. Such an integrated engine-aftertreatment system control can be instrumental in improving engine efficiency and emission reduction performance.
Particle Swarm Optimization Tuning of Fault Tolerant Sliding Mode Control for Quadrotor
Authors: Khatiwada Sital , McCormack John , Thein May-Win
Published: November 2018

Unmanned Aerial Vehicle (UAV) mission success is highly dependent on the robust and reliable performance of individual UAVs. Therefore implementing fault tolerant control to prevent UAV catastrophic failure is critical. In this paper, a control strategy for a Quadrotor under actuator fault is considered. A Sliding Mode Controller (SMC) is used to control the quadrotor during nominal and fault conditions. The gains of the SMC are obtained through a Lyapunov stability analysis, and optimized through Particle Swarm Optimization (PSO). Simulations are presented to exhibit controller effectiveness during nominal and fault conditions.
Varying Motor Assistance During Biceps Curls Induced via Functional Electrical Stimulation
Authors: Rouse Courtney A. , Cousin Christian A. , Duenas Victor H. , Dixon Warren E.
Published: November 2018

Robot-assisted therapy has been established as a useful rehabilitation tool for motor recovery in people with various neurological impairments; however, balancing human and robot contribution, such that the target muscle is sufficiently exercised, is necessary to improve the outcome of rehabilitation protocols. Functional Electrical Stimulation (FES) can assist a person to move their limb by contracting the muscle; however, motor assistance is often necessary to accurately follow a desired limb trajectory, especially since stimulation can be limited due to various factors (e.g., subject comfort, stimulation saturation). In this paper, a motor is tasked with intermittently assisting the FES-activated biceps brachii in tracking a desired forearm trajectory whenever the FES input reaches a pre-set comfort threshold. A Lyapunov-like switched systems stability analysis is used to prove exponential stability of the human-robot system. Preliminary experiments demonstrate the feasibility and performance of the controller on two subjects with neurological impairments.
Control Oriented Dynamic Modeling of a Tension-Leg Platform Based Floating Offshore Wind Turbine With Dynamic Vibration Absorbers
Authors: Wu Zhongyou , Li Yaoyu
Published: November 2018

Due to platform motions, floating offshore wind turbine loads are increased. Among proposed platform concepts, tension leg platform introduces least wind turbine load increase. To reduce wind turbine loads, extra actuators have been added to the platform to suppress the tension leg platform motion. For these actuators controller design, it is critical to derive a mathematical model of the platform-wind turbine-actuator system. In this paper, a reduced 13 DOFs model is derived using Lagrange equation and validated with simulation results from FAST. This reduced model is simple, but accurate enough to predict wind turbine and platform response under wind and wave disturbance. Based on the proposed model, an LQR controller is designed. One simulation case shows that the wind turbine tower load can be effectively reduced by actively controlled DVAs.
Modeling Li-Ion Battery Thermal Runaway Using a Three Section Thermal Model
Authors: Cai Ting , Stefanopoulou Anna G. , Siegel Jason B.
Published: November 2018

This paper presents a model describing lithium-ion battery thermal runaway triggered by an internal short. The model predicts temperature and heat generation from the internal short circuit and side reactions using a three-section model. The three sections correspond to the core, middle, and surface layers. At each layer, the temperature-dependent heat release and progression of the three major side reactions are modeled. A thermal runaway test was conducted on a 4.5 Ah nickel manganese cobalt oxide pouch cell, and the temperature measurements are used for model validation. The proposed reduced order model based on three sections can balance the computational speed with the model complexity required to predict the fast core temperature evolution and slower surface temperature growth. The model shows good agreement with the experimental data, and it will be further improved with formal tuning in a follow-up effort to enable early detection of thermal runway induced by internal short.
On the Multi-Body Modeling and Validation of a Full Scale Wind Turbine Nacelle Test Bench
Authors: Panyam Meghashyam , Bibo Amin , Roach Samuel
Published: November 2018

Ground testing of full-scale wind turbine nacelles has emerged as a highly favorable alternative to field testing of prototypes for design validation. Currently, there are several wind turbine nacelle test facilities with capabilities to perform repeated and accelerated testing of integrated turbine components under loads that the machine would experience during its nominal lifetime. To perform accurate and efficient testing, it is of significant interest to understand the interaction between coupled test rig/dynamometer and nacelle components, particularly when applying extreme loads. This paper presents a multi-body simulation model that is aimed at understanding the responses of a coupled test rig and nacelle system during specific tests. The validity of the model is demonstrated by comparing quasi-static and dynamic simulation responses of key components with experimental data obtained on an actual 7.5 MW test rig. A case study is conducted to analyze a transient grid-loss event; a Low Voltage Ride Through (LVRT) test on the dynamometer and drivetrain components. It is shown that the model provides an efficient way to predict responses of the coupled system during transient/dynamic tests before actual implementation. Recommendations for mitigating the impact of such tests on the test bench drive components are provided. Additionally, observations of differences between transient events in the field and ground based testing are made.
Analytical and Experimental Predictor-Based Time Delay Control of Baxter Robot
Authors: Bagheri Mostafa , Krstić Miroslav , Naseradinmousavi Peiman
Published: November 2018

In this paper, a predictor-based controller for a 7-DOF Baxter manipulator is formulated to compensate a time-invariant input delay during a pick-and-place task. Robot manipulators are extensively employed because of their reliable, fast, and precise motions although they are subject to large time delays like many engineering systems. The time delay may lead to the lack of high precision required and even catastrophic instability. Using common control approaches on such delay systems can cause poor control performance, and uncompensated input delays can produce hazards when used in engineering applications. Therefore, destabilizing time delays need to be regarded in designing control law. First, delay-free dynamic equations are derived using the Lagrangian method. Then, we formulate a predictor-based controller for a 7-DOF Baxter manipulator, in the presence of input delay, in order to track desirable trajectories. Finally, the results are experimentally evaluated.
Simulation Study of a Spherical Inverted Pendulum on an Omnidirectional Cart With Holonomic Constraints
Authors: Maity Sayani , Luecke Greg R.
Published: November 2018

In this paper we develop the control and stabilization of a spherical jointed inverted pendulum balanced on an omnidirectional cart. The system consists of an omnidirectional cart with mecanum wheels equipped with a spherical inverted pendulum attached at the center of the platform. The inverted pendulum is free to fall in any direction perpendicular to the horizontal plane. The omnidirectional cart has the special ability to move in any direction without changing orientation. It can also rotate around its vertical axis. This balancing platform provides a base with holonomic motion to support and balance the pendulum. In this work, the system has been decoupled into two separate subsystems in the x-z and y-z plane. We develop the system dynamic equations in both vertical planes and design a LQR controller to stabilize the system. Using one-dimensional pendulum experimental data, we validate our controller and extend the approach to stabilize the spherical pendulum in both vertical directions. Simulation results are presented to show the effectiveness of the decoupled system LQR controller in stabilizing the spherical pendulum.
Game Theoretic Modeling of a Steering Operation in a Haptic Shared Control Framework
Authors: Ghasemi Amir H.
Published: November 2018

Haptic shared control is expected to achieve a smooth collaboration between humans and automated systems, because haptics facilitate mutual communication. This paper addresses a the interaction between the human driver and automation system in a haptic shared control framework using a non-cooperative model predictive game approach. In particular, we focused on a scenario in which both human and automation system detect an obstacle but select different paths for avoiding it. For such a scenario, the open-loop Nash steering control solution is derived and the influence of the human driver’s impedance and path following weights on the vehicle trajectory are investigated. It is shown that by modulating the impedance and the path following weight the control authority can be shifted between the human driver and the automation system.
Self-Balancing by Design in Hybrid Electrochemical Battery Packs
Authors: Aljunid Nur Adilah , Denlinger Michelle A. K. , Fathy Hosam K.
Published: November 2018

This paper explores the novel concept that a hybrid battery pack containing both lithium-ion (Li-ion) and vanadium redox flow (VRF) cells can self-balance automatically, by design. The proposed hybrid pack connects the Li-ion and VRF cells in parallel to form “hybrid cells”, then connects these hybrid cells into series strings. The basic idea is to exploit the recirculation and mixing of the VRF electrolytes to establish an internal feedback loop. This feedback loop attenuates state of charge (SOC) imbalances in both the VRF battery and the lithium-ion cells connected to it. This self-balancing occurs automatically, by design. This stands in sharp contrast to today’s battery pack balancing approaches, all of which require either (passive/active) power electronics or an external photovoltaic source to balance battery cell SOCs. The paper demonstrates this self-balancing property using a physics-based simulation of the proposed hybrid pack. To the best of the authors’ knowledge, this work represents the first report in the literature of self-balancing “by design” in electrochemical battery packs.
Integration of Multibody System Dynamics With Sliding Mode Control Using FPGA Technique for Trajectory Tracking Problems
Authors: Nada Ayman A. , Bashiri Abdullateef H.
Published: November 2018

Trajectory tracking robotic systems require complex control procedures that occupy less space and need less energy. For these reasons, the development of computerized and integrated control systems is crucial. Recently, developing reconfigurable Field Programmable Gate Arrays (FPGAs) give a prominence of the complete robotic control systems. Furthermore, it has been found in the literature that the model-based control methods are most efficient and cost-effective. This model must interpret how multiple moving parts interact with each other and with their environment. On the other hand, MultiBody Dynamic (MBD) approach is considered to solve these difficulties to attain the models accurately. However, the obtained equations of motion do not match the well-developed forms of control theory. In this paper, the MBD model of a mobile robot is established; and the equations of motion are reshaped into their control canonical form. Additionally, the Sliding Mode Control (SMC) theory is used to design the control law. The constraints’ manifold, which is available in the equations of the MBD system, are imposed systematically as the switching surface. SMC is applied because of its ability to address multiple-input/multiple-output nonlinear systems without resorting any approximations. Eventually, the experimental verification of the proposed algorithm is carried out using DaNI mobile robot in which, a Reconfigurable Input/Output (RIO) board is used to reorient the control design, so that can fit the required trajectory. The control law is implemented using LabVIEW software and NI-sbRIO-9631 with acceptable performance. It is obvious that the integration of MBD/SMC/FPGA can be used successfully to develop embedded systems for the applications of trajectory tracking robotics.
Battery Discharge Strategies for Energy Management in Electrified Truck for Pickup and Delivery Application
Authors: Arasu Mukilan T. , Ahmed Qadeer , Rizzoni Giorgio
Published: November 2018

Fuel economy in a hybrid electric vehicle is significantly affected by the battery discharge strategy. This paper investigates the blended battery discharge strategy with four possible battery State of Charge (SOC) profiles to compare the fuel savings possible over a default Charge Discharge – Charge Sustaining strategy, given that the vehicle’s duty cycle is known. A pickup & delivery truck with Range Extended Electric Vehicle (REEV) powertrain architecture has been modeled. Vehicle speed control is implemented using a distance-based driver that matches the distance traveled from every start to stop in the drivecycle. On-board energy management is implemented using the Energy Consumption Minimization Strategy (ECMS). It is found that a predicted power consumption-based battery discharge profile results in the least fuel consumption. A distance based discharge has relatively higher fuel consumption but is quite close.
Rotary Versus Flapping Flight: An Application Study for Optimal Periodic Control Theory
Authors: Ghanaatpishe Mohammad , Bayiz Yağiz E. , Cheng Bo , Fathy Hosam K.
Published: November 2018

This paper uses optimal periodic control (OPC) theory as a framework for assessing the relative efficiency of revolving versus flapping wing trajectories in insect-sized flight problems. The literature already offers both experimental and simulation-based comparisons between these two flight modes. A collective conclusion from these studies is that the potential advantages of flapping flight depend on many factors such as Reynolds number, wing size/morphology, wing kinematic constraints, aerodynamic efficiency metrics, etc. This makes it necessary to develop a unified framework for comparing these flight modes under various conditions. We address this need by using the π test from OPC theory as a tool for analyzing the degree to which one can improve the efficiency of steady rotary hovering flight through periodic trajectory perturbations. A quasi-steady insect flight model from the literature is adopted as a case study. The paper applies the π test to this model. It then concludes by solving for the optimal lift-power Pareto fronts for both flight modes, and using these Pareto fronts to confirm the results predicted by the π test.
Pursuit Strategies for a Target Tracking Game Around a Circular Obstacle
Authors: Zou Rui , Gao Tianshuang , Bhattacharya Sourabh
Published: November 2018

In this paper, we address a visibility-based target tracking game for the scenario when the environment contains a circular obstacle. The game is originally formulated in four dimensions, but due to the symmetry of the environment, the dimension of the state space can be reduced to three. In the reduced state space, we formulate a game of degree. We use Isaacs techniques to obtain the locally optimal solution of the players. These solutions are extended back in the state space keeping in mind the geometry of the environment to obtain complete solution in the solution. Finally, we construct vector fields whose integral curves are the optimal solutions in the state space.
Vehicle Dynamics of Permanent-Magnet Levitation Based Hyperloop Capsules
Authors: Pradhan Roshan , Katyayan Aditya
Published: November 2018

Hyperloop technology has been proposed in recent years as a novel mode of transportation which has the potential to revolutionize inter-city cargo & passenger transport. This paper aims to establish a benchmark framework for the modelling, simulation and design of the vehicle dynamics of Hyperloop capsules. An analytical treatment of a simplified linearized model is discussed as a starting point for initial parameter optimization. Further, the construction of a full-vehicle nonlinear model is detailed, and the application of this model in the design process is elaborated upon. Though the specific example studied here is that of an externally-propelled, permanent-magnet levitation based Hyperloop vehicle, the discussion can be extended to any levitating dynamical system. The potential applications of Hyperloop technology being vast, a framework such as this may act as a significant contribution to the research and development taking place in the field.
Fault Detection and Isolation for Complex Thermal Management Systems
Authors: Tannous Pamela J. , Alleyne Andrew G.
Published: November 2018

In this paper, a robust unknown input observer-based actuator fault detection and isolation (FDI) scheme is applied on an example aircraft fluid thermal management system (FTMS). System dynamics are modeled using a graph-based approach. A linearized state space model is used in a bank of unknown input observers (UIOs) to generate a set of structured robust (in the sense of disturbance decoupling) residuals. Simulation results show successful actuator FDI in the presence of unknown inputs.
Energy-Efficient Adaptive Robust Control of Vector Thrust UAVs With Unknown Inertia Parameters
Authors: Ding Caiwu , Lu Lu , Wang Cong
Published: November 2018

This paper proposes an energy-efficient adaptive robust tracking control method for a class of fully actuated, thrust vectoring unmanned aerial vehicles (UAVs) with parametric uncertainties including unknown moment of inertia, mass and center of mass, which would occur in aerial maneuvering and manipulation. We consider a novel vector thrust UAV with all propellers able to tilt about two perpendicular axes, so that the thrust force generated by each propeller is a fully controllable vector in 3D space, based on which an adaptive robust control is designed for accurate trajectory tracking in the presence of inertial parametric uncertainties and uncertain nonlinearities. Theoretically, the resulting controller achieves a guaranteed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities. In addition, in the presence of only parametric uncertainties, the controller achieves asymptotic output tracking. To resolve the redundancy in actuation, a thrust force optimization problem minimizing power consumption while achieving the desired body force wrench is formulated, and is shown to be convex with linear equality constraints. Simulation results are also presented to verify the proposed solution.
Decentralized 3D PDE Based Collaborative Trajectory Planning and Target Surrounding for Swarm of UAVs in Cluttered Environment
Authors: Radmanesh Mohammadreza , Kumar Manish , Casbeer David , Cohen Kelly
Published: November 2018

In this paper, we address the decentralized collaborative trajectory planning and target surrounding of multiple Unmanned Air Vehicles (UAVs) in three-dimensional space using Partial Differential Equation (PDE) method. The mission objective is simultaneously arrival of UAVs with safe flight trajectory to a certain radius of an a – priori target. Then by reforming the configuration of swarm, UAVs would circle around the target. The assumption in this work is that the arrival time between the UAVs’ final and initial positions are defined a – priori. The constraints in this paper are (i) Three dimensional Dubins path and UAV dynamic constraints, (ii) Minimum separation distance between UAVs, and (iii) Collision-free trajectory throughout the flight. We define a novel concept of Prediction Set (PS) based on our previous study on PDE path planning method and then we apply the PDE PSs to the constraints of the problem (i.e., (i) to (iii)) and solve the optimization problem. Finally, the concept is demonstrated by numerical simulation and an experiment to represent the effectiveness of the solution.
Energy Implications of Torque Feedback Control and Series Elastic Actuators for Mobile Robots
Authors: Buerger Stephen P. , Mazumdar Anirban , Spencer Steven J.
Published: November 2018

Torque feedback control and series elastic actuators are widely used to enable compact, highly-geared electric motors to provide low and controllable mechanical impedance. While these approaches provide certain benefits for control, their impact on system energy consumption is not widely understood. This paper presents a model for examining the energy consumption of drivetrains implementing various target dynamic behaviors in the presence of gear reductions and torque feedback. Analysis of this model reveals that under cyclical motions for many conditions, increasing the gear ratio results in greater energy loss. A similar model is presented for series elastic actuators and used to determine the energy consequences of various spring stiffness values. Both models enable the computation and optimization of power based on specific hardware manifestations, and illustrate how energy consumption sometimes defies conventional best-practices. Results of evaluating these two topologies as part of a drivetrain design optimization for two energy-efficient electrically driven humanoids are summarized. The model presented enables robot designers to predict the energy consequences of gearing and series elasticity for future robot designs, helping to avoid substantial energy sinks that may be inadvertently introduced if these issues are not properly analyzed.
An Atmospheric Energy Harvester System: Linear Model and Test
Authors: Ganesh Sneha , Schweisinger Todd , Wagner John R.
Published: November 2018

Energy harvesters are steadily gaining popularity as a power source for microelectronic circuits, particularly in wireless sensor nodes and autonomous devices. Energy harvesting from small temperature and/or pressure variations, coupled with an appropriate energy storage unit, can generate sufficient electric power to operate low power electronics. Ongoing research in this area seeks to improve the power capacity and conversion efficiencies of such systems. In this project, a phase change vapor based atmospheric energy harvester with an electromechanical power transformer has been developed. An ethyl chloride fluid system converts the pressure generated, in response to nominal environmental changes, into usable electric power through a mechanical driveline-spring unit and attached DC generator. Published numerical results have indicated 9.6 mW power generation capacity over a 24 hour period for a low frequency sinusoidal temperature input with ±1°C variation at standard pressure. A prototype electromechanical unit was fabricated and experimentally tested; 30 mW electric power for a resistance load was recorded using an emulated input corresponding to 50 bidirectional cyclic atmospheric variations (∼175 hour period). Linearized models were derived to help evaluate the system’s transient characteristics and these mathematical results agreed favorably with the experimental behavior.
Enhanced Vibration Energy-Harvesting Using Inerter-Based Two-Degree-of-Freedom System
Authors: Liu Mingyi , Tai Wei-Che , Zuo Lei
Published: November 2018

In rotational electromagnetic generator based vibration energy-harvesting systems, the generator rotor is an inerter. From analysis, it is found that the inerter decreases system frequency bandwidth in single-degree-of-freedom (SDOF) energy-harvesting systems. The maximum electric power output of a SDOF system is limited by mechanical damping and maximum stroke that allowed. Two-degree-of-freedom (2DOF) energy-harvesting systems was proposed in recent years and has been shown to have the potential to have better power, power/stroke ratio, and frequency bandwidth performance compared with SDOF systems. However, extra mass has to be added in most of the case. In this paper, a new design of inerter-based-2DOF energy-harvesting system was proposed by adding a spring in series with the inerter in SDOF system. No extra mass is added compared with its counterpart SDOF system. Optimal specific power at limited stroke were obtained by tuning system parameters, which includes resonance frequency ratio, spring ratio, mass ratio, and damping ratio. The contribution of each parameter to system performance was analyzed. The results show that the proposed inerter-based-2DOF system has better performance compared with the SDOF system. The inerter-based-2DOF can have larger specific power and larger power/stroke ratio over a wider frequency bandwidth. Simulation also show that improved performance not only obtained with sinusoidal excitation with constant displacement amplitude, but also with sinusoidal excitation with constant force amplitude.
Rapid Probe Engagement and Withdrawal With Online Minimized Probe-Sample Interaction Force in Atomic Force Microscopy
Authors: Wang Jingren , Zou Qingze
Published: November 2018

In this paper, the problem of rapid probe engagement and withdrawal in atomic force microscopy (AFM) is addressed. Probe engagement to and withdrawal from the sample, respectively, are fundamental steps in all AFM operations, ranging from imaging to nanomanipulation. However, due to the highly nonlinear force-distance relation and the rapid transition between the attractive and the repulsive force dominance, a quick “snap-in” of the probe and excessively large repulsive force during the engagement, and a large adhesive force during the withdrawal are induced, resulting in sample deformation and damage, and measurement errors. Such adverse effects become more severe when the engagement and withdrawal is at high speeds, and the sample is soft (such as the live biological samples). Rapid engagement and withdrawal is needed to achieve high-speed AFM operations, particularly, to capture and interrogate dynamic evolutions of the sample. We propose a learning-based online optimization technique to minimize the probe-sample interaction force in high-speed engagement and withdrawal. Specifically, the desired force and probe position trajectory profile is online designed by using the optimal trajectory design technique, and tracked by using iterative learning control technique. Then the designed force-trajectory profile is online optimized to minimize the engagement force and the adhesive force. The proposed rapid engagement and withdrawal technique is illustrated through experimental implementation on a Polydimethylsiloxane (PDMS) sample.
Validating DC Motor Models on the Quanser Qube Servo
Authors: Reck Rebecca M.
Published: November 2018

DC motors are popular for many engineering applications such as robotics, aerospace, home automation, and many others. As such, they are also popular systems for undergraduate examples and instructional laboratories in engineering. Many of these examples use a standard first-order model of a DC Motor using first principles modeling to derive the parameters. However, not much emphasis is placed on how well these models match the actual data. In this paper, six DC motor models, including three frequently found in textbook examples, will be compared to recorded data from actual DC motors in order to develop a model that represents the actual physical behavior of a DC motor. The models that were developed from the data rather than first principles matched the data more closely for the angular velocity output of the motor. Finally, the best models will be used to simulate a closed-loop position control of the motor and match the performance to recorded data.
Optimal Scheduling of Home Energy Management System With Plug-In Electric Vehicles Using Model Predictive Control
Authors: Zhao Yue , Chen Yan , Keel Brian
Published: November 2018

For a household microgrid with renewable photovoltaic (PV) panel and plug-in electric vehicles (PEVs), a home energy management system (HEMS) using model predictive control (MPC) is designed to achieve optimal PEV charging and energy flow scheduling. Soft electric loads and an energy storage system (ESS) are also considered in the optimization of PEV charging in the MPC framework. The MPC is solved through a mixed-integer linear programming (MILP) by considering the relationship of energy flows in the optimization problem. Through the simulation results, the performance of optimization results under various electricity price plans is evaluated. The influences of PV capacities on the optimization results of electricity cost are also discussed.
Partitioned Adaptive Control Based on Neural Network of a Flexible Space Robot After Capture Operation
Authors: Cheng Jing , Chen Li , Liang Jianxun , Ma Wei
Published: November 2018

The partitioned adaptive control and vibration suppression of free-floating space robot with flexible arms in post-impact process are studied. At first, the dynamic model of combination system after flexible space robot system capturing a target system is established based on the collision theory; the impact effect of space robot combination system after capture operation is analyzed at the same time. Secondly, based on the double time scale decomposition theory, the unstable combination system is decomposed into fast system and slow system, representing the rigid motion of the system and the flexible vibration respectively. To satisfy the compute capacity of space-borne computer and modular design concept, the slow system is considered as a set of interconnected subsystems and a decentralized adaptive neural network control scheme is designed. Neural network is applied to approximating the unknown dynamic of the subsystems; an adaptive sliding mode controller is designed to eliminate both interconnection term and approximation error. The control algorithm has a cutting edge in independent control signal and reduced calculation amount. The Linear Quadratic Optimal control scheme is designed for fast system to suppress the elastic vibration of the flexible manipulators. At last, numerical example demonstrates the validity of the proposed composite control scheme.
Analytical Study of a Piezoelectric Frequency Up-Conversion Harvester Under Sawtooth Wave Excitation
Authors: Onsorynezhad Saeed , Abedini Amin , Wang Fengxia
Published: November 2018

In this work, an impact based frequency up-conversion mechanism is studied via discontinuous dynamics analysis. The mechanism consists of a moving stopper and a piezoelectric beam. The repeated free vibration of the piezoelectric beam achieved through the impaction between the stopper and the beam, With the stopper excited by a sawtooth wave. Due to the impact, the system contains complex discontinuous dynamics, hence to better understand the energy harvesting performance of the piezoelectric beam, we seek the simple periodic motions of the system. As the system parameter varies, the output voltage and power of the piezoelectric beam with periodic motions is obtained. These results were also compared with those obtained when the piezoelectric beam is directly subjected to the same sawtooth wave.

The piezoelectric beam was modeled as a mass-spring-damper system, and the linear piezoelectric constitutive equations have been used to obtain the lumped model of the piezoelectric beam. In this study, numerical solutions of the generated power and voltage were obtained via discontinuous dynamics analysis. When the excitation frequency is low, the effect of frequency-up-conversion is demonstrated by comparing the generated power of two cases: piezoelectric beam excited via impact and beam directly subject to the sawtooth wave. The stable and unstable periodic motions and bifurcation trees of the impact parameters are predicted analytically versus varying excitation frequency for period-1 and period-2.
Trust-Based Runtime Verification for Multi-Quad-Rotor Motion Planning With a Human-in-the-Loop
Authors: Mahani Maziar Fooladi , Wang Yue
Published: November 2018

In this paper, we propose a trust-based runtime verification (RV) framework for deploying multiple quad-rotors with a human-in-the-loop (HIL). By bringing together approaches from runtime verification, trust-based decision-making, human-robot interaction (HRI), and hybrid systems, we develop a unified framework that is capable of integrating human cognitive skills with autonomous capabilities of multi-robot systems to improve system performance and maximize the intuitiveness of the human-robot-interaction. On top of the RV framework, we utilize a probabilistic trust inference model as the key component in forming the HRI, designed to maintain the system performance. A violation avoidance controller is designed to account for the unexpected/unmodeled environment behaviors e.g. collision with static/moving obstacles. We also use the automata theoretic approaches to generate motion plans for the quad-rotors working in a partially-known environment by automatic synthesis of controllers enforcing specifications given in temporal logic languages. Finally, we illustrated the effectiveness of this framework as well as its feasibility through a simulated case study.
The Secant Method: Global Trajectory Planning With Variable Radius, Solid Obstacles
Authors: Ahlin Konrad J. , Sadegh Nader , Hu Ai-Ping
Published: November 2018

Artificial Potential Field (APF) theory is a unique branch of robotic path planning, which could be capable of handling the need for high dimensional robotic obstacle avoidance. However, APF theories have general performance issues which often make them undesirable in application. This research analyzes the Secant Approach; an algorithm developed to follow the APF style of path planning, but which has guaranteed convergence and obstacle avoidance properties in n-dimensional space. Using a unique potential function, the Secant Approach can guarantee a global minimum at the target while provably eliminating local minimums at other locations. Also, a control scheme has been developed which has guaranteed convergence properties. The Secant Approach is therefore capable of guiding various forms of robotic applications to target positions in n-dimensional space, making the theory a powerful path planning tool. This analysis examines the structure of the Secant Approach and extends the theory to include variable radius, solid obstacles.
Predictively Coordinated Vehicle Acceleration and Lane Selection Using Mixed Integer Programming
Authors: Dollar R. Austin , Vahidi Ardalan
Published: November 2018

Autonomous vehicle technology provides the means to optimize motion planning beyond human capacity. In particular, the problem of navigating multi-lane traffic optimally for trip time, energy efficiency, and collision avoidance presents challenges beyond those of single-lane roadways. For example, the host vehicle must simultaneously track multiple obstacles, the drivable region is non-convex, and automated vehicles must obey social expectations. Furthermore, reactive decision-making may result in becoming stuck in an undesirable traffic position. This paper presents a fundamental approach to these problems using model predictive control with a mixed integer quadratic program at its core. Lateral and longitudinal movements are coordinated to avoid collisions, track a velocity and lane, and minimize acceleration. Vehicle-to-vehicle connectivity provides a preview of surrounding vehicles’ motion. Simulation results show a 79% reduction in congestion-induced travel time and an 80% decrease in congestion-induced fuel consumption compared to a rule-based approach.
Optimal Exhaust Valve Opening Control for Fast Aftertreatment Warm Up in Diesel Engines
Authors: Salehi Rasoul , Stefanopoulou Anna G.
Published: November 2018

This paper proposes to optimally adjust the exhaust valve opening (EVO) timing for faster selective catalytic reduction (SCR) aftertreatment system warm-up during the cold start phase of the federal test procedure (FTP). Early termination of the power stroke by EVO timing advance increases the engine exhaust gas temperature. It, on the other hand, causes exhaust flow rate reduction that decreases the coefficient of the heat transfer from the exhaust gas to the catalyst. The competing effects along with the fuel consumption increase associated with early EVO need careful consideration and the optimal EVO timing is a load-dependent balance of all these effects. This careful balance is achieved in this paper by dynamic programing (DP). Specifically, the minimum time to light-off (TTL) is formulated and applied to the cold phase of the FTP. A high fidelity detailed and verified engine and aftertreatment model is effectively simplified to enable utilizing computationally expensive DP optimization algorithm. Optimization results indicate that advancing the EVO reduces the TTL for the SCR catalyst from 659 s to 500 s, a 24% reduction. This fastest possible increase in the SCR temperature is shown to be with an expense of 4.1% increase in the fuel consumption. The results are dependent to the target light-off temperature and the load profile. Assuming a specific light-off temperature and the FTP, possible rule-based scenarios for online optimization are discussed.
Controller Design for Two-Input Single-Output Systems Exploiting Plant/Controller Alignment
Authors: Weir Nathan A. , Alleyne Andrew G.
Published: November 2018

Due to the unique structure of TISO feedback systems, several closed loop properties can be characterized using the concepts of plant and controller “directions” and “alignment”. Poor plant/controller alignment indicates significant limitations in terms of closed loop performance. In general, it is desirable to design a controller that is well aligned with the plant in order to minimize the size of the closed loop sensitivity functions and closed loop interactions. Although the concept of alignment can be a useful analysis tool for a given plant/controller pair, it is not obvious how a controller should be designed to achieve good alignment. We present a new controller design approach, based on the well-known “PQ method”, which explicitly incorporates knowledge of alignment into the design process. This is accomplished by providing graphical information about the alignment angle on the Bode plot of the PQ frequency response. We show the utility of this approach through a design example.
Sliding Mode Impedance Control of a Hydraulic Artificial Muscle
Authors: Slightam Jonathon E. , Nagurka Mark L. , Barth Eric J.
Published: November 2018

Hydraulic artificial muscles offer unrivaled specific power and power density and are instrumental to the improved performance and success of soft robotics and lightweight mobile applications. This paper addresses the lack of model-based impedance control approaches for soft actuators such as hydraulic artificial muscles. Impedance control of actuators and robotic systems has been proven to be an effective approach for interacting with physical objects in the presence of uncertainty. A sliding mode impedance control approach based on Filippov’s principle of equivalent dynamics is introduced and applied to a hydraulic artificial muscle. A nonlinear lumped parameter model of the system is presented and a sliding mode impedance controller is derived. Experimental results show superior performance using model-based sliding mode impedance control versus a linear impedance control law in both tracking of position and stiffness when disturbances are introduced.
Fused Closed-Loop Flight Dynamics and Wake Interaction Modeling of Tethered Energy Systems
Authors: Deese Joe , Razi Peyman , Muglia Michael , Ramaprabhu Praveen , Vermillion Chris
Published: November 2018

In this paper, we present a fused flight dynamics and wake interaction modeling framework for arrays (farms) of tethered wind and marine hydrokinetic energy systems. The replacement of conventional towers with tethers necessitates a dynamic model that captures the flight characteristics of each system, whereas the arrangement of the systems in an array necessitates a wake interaction model. The integration of these components is unique to the tethered energy systems literature and is applicable to both airborne wind energy systems and tethered marine hydrokinetic energy systems. In the application case study of this paper, we focus specifically on arrays of ocean current turbines (OCTs), which are intended to operate in the deep waters of the Gulf Stream, adjacent to the eastern coast of the United States. In particular, we evaluate the dynamic performance and resulting projected energy output of an array of tethered OCTs, based on real Gulf Stream resource data from an acoustic Doppler current profiler (ADCP) located adjacent to Cape Hatteras, North Carolina.
Design and Validation of a Torque Controllable Hip Exoskeleton for Walking Assistance
Authors: Kang Inseung , Hsu Hsiang , Young Aaron J.
Published: November 2018

Recent technological advancements have expanded the field of human augmentation. Specifically, lower limb exoskeletons have benefited many by providing assistance to increase mobility. The proposed study aims to develop a novel bilateral hip exoskeleton that provides mechanical power assistance in both hip flexion and extension during walking. Each actuation unit employs series elastic actuator for a high fidelity closed loop torque control utilizing a ball screw transmission incorporated with a fiberglass leaf spring. The control architecture was divided into three tiers and each tier implemented different control algorithms. The device was experimentally validated with both benchtop and human testing. Benchtop testing was done to tune required control parameters in the low-level controller and to validate the torque response. We tested five able-bodied subjects walking with our device. We analyzed their kinematic and kinetic data with different levels of mechanical power assistance during walking. Our benchtop testing results showed that the low-level PID gains were tuned to achieve desired bandwidth and torque tracking. Human testing results demonstrated that the high-level controller provided an accurate information for assistance onset timing that the hip exoskeleton was able to assist the user effectively.
Experimental Investigation on Vibration Damping Characteristics of Magnetorheological Damper
Authors: Cheng Ming , Chen Zhaobo , Mahmoodi S. Nima
Published: November 2018

This paper studies the vibration damping characteristics of a magnetorheological (MR) damper. A single-degree-of-freedom vibration isolation system with pedestal motion containing MR dampers has been experimentally investigated. Results show that the transmissibility at the resonance frequency does not constantly decrease as expected. It gradually decreases at the beginning, then increase unexpectedly as the input current increases. In addition, the resonant frequency of the system increases continuously. In order to explore the mechanism behind the experimental phenomenon, a centralized parameterized model of the MR damper is established. Hardening coefficient, a parameter that characterizes the dynamic characteristics of the MR damper is introduced, and the influence of the structural parameters and dynamic parameters of the MR damper on the hardening coefficient is analyzed. Simultaneously, a dynamic model of the MR damper is derived based on the Bingham model, and the damping characteristics of the MR damper are predicted and compared with the experimental results. Further, based on a simplified and equivalent dynamic model of the system, the relationship between transmissibility of the system and load mass, stiffness, and damping reveals the physical laws behind the experimental phenomenon. Finally, theoretical results are derived and compared with the experimental results, which demonstrates the rationality of the theoretical analysis.
Stochastic Stability of a Piezoelectric Vibration Energy Harvester and Stabilization Using Noise
Authors: Ramakrishnan Subramanian , Edlund Connor
Published: November 2018

Vibration energy harvesters convert the energy of ambient, random vibration into electrical power often using piezoelectric transduction. The stochastic dynamics of a piezoelectric harvester with parameteric uncertainties is yet to be fully explored in the nonequilibrium regime. Motivated by mathematical results that establish the counterintuitive phenomenon of stabilization of response in certain nonlinear systems using noise, we investigate the stochastic stability of a generic harvester in the linear and the monostable nonlinear regimes excited by multiplicative noise characterized by both Brownian and the Lévy stable distributions. First, a lower bound on the magnitude of noise intensity that guarantees exponential stability almost surely, is obtained analytically as an inequality in terms of system parameters in the linear case. This result is validated numerically using the Euler-Maruyama scheme. Next, noise-induced stabilization in the harvester dynamics is demonstrated numerically for both the linear and nonlinear cases wherein Lévy noise was found to achieve stabilization at lower noise intensities than Brownian noise. Additionally, the inclusion of a nonlinear stiffness does not have an appreciable affect on the stabilization behavior. The results indicate that stabilization may be achieved using noise and are expected to be useful in harvester design.