bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cutting the Deployment Costs of Physics-Based MPC in Buildings by Simulation-Based Imitation Learning
Authors: Drgona Jan , Helsen Lieve , Vrabie Draguna L. 
Published: January 2021

Abstract
It has been shown that model predictive control (MPC) is a promising solution for energy-efficient building operations. However, the deployment of MPC in a large portion of the building stock has not been possible partially because of high installation costs. Every building is unique and requires a tailored MPC solution. The best performing solutions are often based on physics-based modeling, which is, however, computationally expensive and requires dedicated software. A promising direction that tackles this problem is to train a neural network-based optimal control policy to imitate the behavior of physics-based MPC from the simulation data generated offline. The neural networks give control actions that closely approximate those produced by physics-based MPC, but with a fraction of the computational and memory requirements and without the need for licensed software. The main advantage of the proposed approach stems from simple evaluation at execution time, leading to low computational foot-prints and easy deployment on embedded HW platforms. In the case study, we present the energy savings potential of physics-based MPC applied to an office building in Belgium. We demonstrate how neural network approximators can be used to cut the implementation and maintenance costs of MPC deployment without compromising performance. We also critically assess the presented approach by pointing out the remaining challenges and open research questions.
Temperature Sensor Deployment for Scalable Battery Packs
Authors: Gao Mengzhu , Lai Qingzhi , Lin Xinfan 
Published: January 2021

Abstract
Li-ion battery systems have been widely used as an essential power source in many applications. To ensure the safety and longevity of the system, a battery pack thermal model is often used in combination with distributed temperature sensors for thermal management and monitoring purposes. Due to the limited number of sensors and sparse measurement, sensor deployment to maximize the observability of the system thermal dynamics has been a critical topic, which has attracted research attention but remains to be resolved. This paper is devoted to exploring the pattern of optimal sensor locations for scalable battery systems under different observability criteria. A battery pack thermal model is first developed based on a single cell thermal model and considering the thermal interconnection between cells in the pack. Sensor location optimization is then performed by maximizing two Gramian-based observability metrics, which quantify different aspects of system observability. Optimal sensor locations obtained under the two metrics are analyzed and compared for battery systems of different sizes. Based on the results, deployment patterns of optimal sensor locations are extracted and analyzed theoretically by correlating to the physics of the battery thermal dynamics. Moreover, the influences of critical parameters of battery packs on system observability are also analyzed and discussed.
A Cellular Automata Model for Dynamics and Control of Cardiac Arrhythmias
Authors: Gallenberger Danny , Xiong Min , Zhuang Tony Z. , Sun Kai , Tolkacheva Elena G. , Zhao Xiaopeng 
Published: January 2021

Abstract
As a leading cause of death in 325,000 adults per year in the United States, a significant proportion of sudden cardiac arrest (SCA) result from arrhythmias. To better understand the onset of arrhythmias and its potential treatment with more rapid and effective control approaches, a two-dimensional 50 × 50 cellular automata (CA) model is used in this study to illustrate the propagation of electrical waves across its tissue, and a constant diastolic interval (DI) control mechanism is adopted to help stabilize and prevent cardiac arrhythmias. Simulations of various scenarios including normal conduction and spiral waves in the presence of scar, normal conduction and alternans under control conditions are shown. The results validate that the CA model and constant DI control method are very efficient and effective in the study of dynamics and control of cardiac arrhythmias.
The Swirling Pendulum: Conceptualization, Modeling, Equilibria and Control Synthesis
Authors: Kadam Sujay D. , Shah Utsav , D’Souza Alrick , Shanthamurthy Prajwal Gowdru , Raj Nidhish , Banavar Ravi N. , Palanthandalam-Madapusi Harish J. 
Published: January 2021

Abstract
This paper introduces the swirling pendulum, a two-link, two degree-of-freedom mechanism which is under-actuated and has an unusual non-planar coupling with axis of rotation of the two links being perpendicular to each other. The swirling pendulum mechanism, while being simple to mathematically represent and easy to physically construct, exhibits several properties like loss of inertial coupling, loss of relative degree, multiple stable and unstable equilibrium points. These properties are unique as well as interesting from dynamics and controls point of view which make the swirling pendulum an excellent test-bed for testing various ideas in control and demonstrating several notions associated with systems and control theory. In this paper, we discuss the modeling of the swirling pendulum mechanism based on Lagrange’s equation along with an analysis related to equilibrium points and their stability. We also present simulation results for regulatory as well as tracking control tasks through simulations on a non-linear model using control methods like LQR, lead compensator and system inversion-based control to demonstrate the utility of the proposed mechanism in the area of systems, control and dynamics. Furthermore, we also discuss experimental results for controls applied on a real-time hardware setup.
The Effects of Trailer Towing on the Dynamics of a Lane-Keeping Controller
Authors: Vörös Illés , Takács Dénes 
Published: January 2021

Abstract
The main question this paper aims to address is whether a lane-keeping controller can serve as a safety feature in order to increase handling and stability of car-trailer combinations. The derivation of a nonholonomic car-trailer model is provided and its open-loop stability is analyzed. A look-ahead based lane-keeping controller is applied to the system, and a comparison is made between the closed-loop stability of an individual car and a car-trailer setup. The critical speed of the vehicle combination is shown as a function of various trailer parameters, with and without the lane-keeping controller enabled. A modified version of the controller is also tested, utilizing feedback of the trailer states. This ensures that the trailer is also kept at the center of the lane, but no improvement was found in terms of stable trailer configurations.
New Stability Analysis and Design of Discrete Time Delay Control for Nonaffine Nonlinear Systems
Authors: Reddy Suresh B. 
Published: January 2021

Abstract
Time Delay Control (TDC) for linear and nonlinear systems with uncertain dynamics has been widely discussed in the literature, as it has a very simple and compact form. It uses time-delayed signals for estimating unknown dynamics at an instant, and uses feedback linearization for cancellation of known and estimated unknown dynamics. While the original formulation and most of the analyses have been focused on the continuous version of the controller, its implementation is more natural in digital form. This paper extends the recently improved sufficient Bounded Input - Bounded Output (BIBO) stability conditions for continuous Time Delay Control of nonaffine nonlinear systems to discrete Time Delay Control, including simplified approximate conditions under various assumptions. Additionally. asymptotic stability is established for similar conditions. The derived conditions are contrasted with earlier results for continuous Time Delay Control. Examples are used to illustrate the differences in continuous and discrete TDC, related to performance as well as sufficient and actual conditions for stability.
Input Excitation Analysis for Black-Box Quadrotor Model System Identification
Authors: Angarita John , Doyle Daniel , Gargioni Gustavo , Black Jonathan 
Published: January 2021

Abstract
System identification provides a process to develop different dynamic models of varying structures based on user-defined requirements. For a quadrotor, system identification has been primarily in the field of off-white and grey-box models, but black-box models have the advantage of incorporating nonlinear aero-dynamic effects while also maintaining performance. For the identification, both a chirp and Hebert-Mackin parameter identification method waveform are used as inputs to maximize excitation while minimizing nonlinear responses. The quadrotor structure is defined by the an autoregressive with exogenous input (ARX) model, an autoregressive-moving-average (ARMAX) model, and a Box-Jenkins (BJ) models and then identified with the prediction error method. The black-box method shows that it maintains identification performance while improving upon the flexibility of different cases and ease of implementation.
Development of Wire Actuated Monolithic Soft Gripper Positioned by Robot Manipulator
Authors: Gutierrez Rafael Barreto , Garcia Martin , McDuffie Joan , Long Courtney , Tekes Ayse 
Published: January 2021

Abstract
This paper presents the design and development of a two fingered, monolithically designed compliant gripper mounted on a two-link robot. Rigid grippers traditionally designed by rigid links and joints might have low precision due to friction and backlash. The proposed gripper is designed as a single piece compliant mechanism consisted of several flexible links and actuated by wire through a servo motor. The gripper is attached to a two-link arm robot driven by three step motors. An additional servo motor can also rotate the base of the robot. While the robot is 3D printed using polylactic acid (PLA), the gripper is 3D printed in thermoplasticpolyurethane (TPU). Two force sensors are attached to the right and left ends of the gripper to measure grasping force. Experimental testing for grasping various objects having different sizes, shapes and weights is carried out to verify the robust performance of the proposed design. Through the experimentation, it’s been noted that the compliant gripper can successfully lift up objects at a maximum mass of 200 g and have a better performance if the objects’width is closer to the width of the gripper. The presented mechanism can be utilized as a service robot for elderly people to assist them pick and place objects or lift objects if equipped with necessary sensors.
Nonlinear Hierarchical MPC for Maximizing Aircraft Thermal Endurance
Authors: Leister Daniel D. , Koeln Justin P. 
Published: January 2021

Abstract
In modern high-performance aircraft, the Fuel Thermal Management System (FTMS) plays a critical role in the overall thermal energy management of the aircraft. Actuator and state constraints in the FTMS limit the thermal endurance and capabilities of the aircraft. Thus, an effective control strategy must plan and execute optimized transient fuel mass and temperature trajectories subject to these constraints over the entire course of operation. For the control of linear systems, hierarchical Model Predictive Control (MPC) has shown to be an effective approach to coordinating both short- and long-term system operation with reduced computational complexity. However, for controlling nonlinear systems, common approaches to system linearization may no longer be effective due to the long prediction horizons of upper-level controllers. This paper explores the limitations of using linear models for hierarchical MPC of the nonlinear FTMS found in aircraft. Numerical simulation results show that linearized models work well for lower-level controllers with short prediction horizons but lead to significant reductions in aircraft thermal endurance when used for upper-level controllers with long prediction horizons. Therefore, a mixed-linearity hierarchical MPC formulation is presented with a nonlinear upper-level controller and a linear lower-level controller to achieve both high performance and high computational efficiency.
Multiple Sliding Surface Controller for a Quadrotor for Improved Robustness Against Wind Disturbances
Authors: Sudakar Madhavan , Sridhar Siddharth , Kumar Manish 
Published: January 2021

Abstract
In this paper, we present a controller design for a quadrotor by obtaining the derivative of the actual control input using the concept of multiple sliding surfaces and Lyapunov stability analysis. The conventional sliding mode controller is highly robust. The discontinuous part of the control input suppresses disturbances well. Theoretically, however, this discontinuity causes rapid switching of the control input (chattering) which results in large energy consumption and inefficiency. The proposed control method formulates the derivative of control input (having the discontinuity) which upon integrating provides a smoother control input when compared to the classical sliding mode control. The quadrotor with our proposed controller is subjected to varying wind disturbance scenarios and its performance is bench-marked against a PID controller and a conventional sliding mode controller. A saturation function sat is used instead of the sign for the classical sliding mode controller as well as the the proposed novel controller design in all sections from 4.2. The reasoning behind this is discussed in the results section of the paper.
Visual Navigation of Wheeled Mobile Robots Using Deep Reinforcement Learning: Simulation to Real-Time Implementation
Authors: Nwaonumah Ezebuugo , Samanta Biswanath 
Published: January 2021

Abstract
A study is presented on applying deep reinforcement learning (DRL) for visual navigation of wheeled mobile robots (WMR), both in simulation and real-time implementation under dynamic and unknown environments. The policy gradient based asynchronous advantage actor critic (A3C), has been considered. RGB (red, green and blue) and depth images have been used as inputs in implementation of A3C algorithm to generate control commands for autonomous navigation of WMR. The initial A3C network was generated and trained progressively in OpenAI Gym Gazebo based simulation environments within robot operating system (ROS) framework for a popular target WMR, Kobuki TurtleBot2. A pre-trained deep neural network ResNet50 was used after further training with regrouped objects commonly found in laboratory setting for target-driven visual navigation of Turlebot2 through DRL. The performance of A3C with multiple computation threads (4, 6, and 8) was simulated and compared in three simulation environments. The performance of A3C improved with number of threads. The trained model of A3C with 8 threads was implemented with online learning using Nvidia Jetson TX2 on-board Turtlebot2 for mapless navigation in different real-life environments. Details of the methodology, results of simulation and real-time implementation through transfer learning are presented along with recommendations for future work.
Sensing and Classification of Ambient Vortex Wake From the Kinematics of a Bioinspired Swimming Robot Using Neural Networks
Authors: Pollard Beau , Tallapragada Phanindra 
Published: January 2021

Abstract
The ability of a swimming robot to extract information from a vortex field in the ambient fluid flow has immense practical applications. Such capabilities perhaps augmented with other sensors are useful to detect and avoid obstacles or potential adversaries in the fluid. This has led many researchers to attempt to sample the pressure field on the surface of a swimmer and thus extract information about the fluid flow such as the flow velocity and angle of attack. In contrast in this paper, we show through simulations, that the kinematic information of a swimmer, specifically its angular velocity, can be used to train a neural network, that can classify the vortex wake in the surrounding fluid. In effect, this classifies the type of body (or its motion) that generates the ambient wake. In practice, the angular velocity of a body can be measured with much greater accuracy than the pressure distribution on the body. We further show that a swimmer with a passive tail-like appendage can classify the vortex field with greater accuracy than a swimmer without such an appendage. Thus the results demonstrated in this paper can be of significant use in designing aquatic robots with passive appendages with improved capabilities of sensing and classifying the ambient flow.
Control Design for Automated Vehicle Emergency Safe Stop System Based on Differential Dynamic Programming
Authors: Yang Lisheng , Furukawa Tomonari , Zuo Lei , Doerzaph Zachary 
Published: January 2021

Abstract
This paper presents the control algorithm and system design for a newly proposed automated emergency stop system, which aims to navigate the vehicle out of its travel lane to a safe road-side location when an emergency (e.g. driver fails to take control during fallback of the Dynamic Driving Task) occurs. To address the unique requirements of such a system, control techniques based on differential dynamic programming are developed. Optimal control sequence computation is broken down into step-by-step quadratic optimization and solved iteratively. Control constraints are addressed efficiently by a tailored Projected-Newton algorithm. The iterative control algorithm is then integrated into a real-time control system which considers both computation delay and modeling errors. The system employs a novel grid-based storage structure for recording all acceptable control commands computed within the iteration and uses a high frequency estimator for self-localization. During operation, the real-time control thread will extract commands from the grid cell corresponding to current states. Simulation results show strong potential of the proposed system for addressing the engineering challenges of the automated emergency stop function. The robustness of the system in presence of computation time delay and modelling errors is also demonstrated.
Lean thinking: using 6S and visual management for efficient adverse event closure
Authors: Alzahrani Ziad 
Published: January 2021

BackgroundWe focused on a busy Adult Oncology Department having over 130 staff members, with around 70 of them being physicians with different levels of specialties. A multidisciplinary committee was formed in the department, consisting of physicians, nurses, pharmacists, a medication safety representative and a quality specialist to look after all reported incidents.Local problemThe department staff at the institution in question in this study expressed their concern about the surging number of reported incidents, delays in closing reports within the set timeframe, ambiguity of individuals’ roles at the committee level and errors in using the safety reporting system (SRS). Accordingly, this study focused on the development of a visual aid through the creation of a functional process map to help clarify team roles and stipulate the steps for adverse event closure.MethodsTheSort,Set-in order,Shine,Standardise,Sustain andSafety and visual management lean principles, as well as the eight lean wastes—Transportation, Inventory, Motion, Waiting, Overprocessing, Overproduction, Defect and Staff underutilisation—were introduced in early May 2016 and used during SRS committee meetings over 3 years.InterventionThe indicators used were the average number of days for both medication and non-medication incidents from the day of reporting until the closure. The extent that the limit was exceeded was compared.ResultsThe average number of days until closure showed a reduction from 67 to 37 and 134 to 61 between Periods I (2016) and III (2018) for medication and non-medication incidents, respectively.ConclusionsThe developed process map was a useful communication tool. It helped to sort process activities, team roles and streamline the process. It brought the average number of days until closure within the acceptable 45-day limit for medication incidents. Thus, using visual aids in the working environment is helpful in improving communication among the workers.
Relationship between afternoon napping and cognitive function in the ageing Chinese population
Authors: Cai Han , Su Ning , Li Wei , Li Xia , Xiao Shifu , Sun Lin 
Published: January 2021

BackgroundSeveral studies have shown that afternoon napping promotes cognitive function in the elderly; on the other hand, some studies have shown opposite results. This current study further examined the relationship between afternoon napping and cognitive function in the ageing Chinese population.MethodsA total of 2214 elderly were included (napping group: n=1534; non-napping group: n=680). They all received cognitive evaluations by the Beijing version of the Montreal Cognitive Assessment, the Mini-Mental State Examination, and the Chinese version of the Neuropsychological Test Battery. Among all the subjects, 739 elderly volunteered to take blood lipid tests.ResultsSignificant differences in cognitive function and blood lipids were observed between the napping and the non-napping groups. Afternoon napping was associated with better cognitive function including orientation, language, and memory in the present study. Subjects with the habit of afternoon napping also showed a higher level of triglyceride than the non-napping subjects.ConclusionThe results demonstrated that afternoon napping was related to better cognitive function in the Chinese ageing population.
Analysis of on-pack messages for e-liquids: a discrete choice study
Authors: Hoek Janet , Gendall Philip , Eckert Christine , Louviere Jordan , Ling Pamela , Popova Lucy 
Published: January 2021

BackgroundPolicymakers wishing to encourage smokers unable to quit to switch to using electronic nicotine delivery systems (ENDS) also need to consider how to deter ENDS use among non-smokers. We examined whether reduced-risk messages could increase ENDS’ appeal among smokers and if increased-risk messages could decrease appeal among susceptible non-smokers, occasional and former smokers.MethodologyAn online discrete choice experiment tested three attributes: information message, nicotine content (0 mg or 3 mg) and flavour (tobacco, menthol or fruit). The sample comprised 352 current smokers, 118 occasional and former smokers, and 216 ENDS-susceptible never smokers. Smokers viewed reduced-risk messages that encouraged switching to ENDS, while other groups viewed increased-risk messages that discouraged ENDS use. All groups saw a typical addiction warning. We analysed the data by estimating multinomial logit regression and adjusted latent class analysis models.ResultsRelative to no message, reduced risk-messages increased the appeal of ENDS uptake among one class of smokers (33.5%) but decreased appeal among other smokers. However, among all smokers, reduced-risk messages increased preference more than a dissuasive addiction warning. By contrast, among occasional or former smokers, and susceptible non-smokers, all information messages discouraging ENDS use, including an addiction warning, decreased preference relative to no message.ConclusionsOn-pack relative-risk messages about ENDS could make transition more attractive to smokers while increased-risk messages could deter ENDS uptake among susceptible non-smokers, occasional and former smokers. Communicating diverse messages via discrete channels could recognise heterogeneity among and between smokers and non-smokers.