bluuebunny/crossref_metadata_2025 huggingface dataset:
Model Reduction and Optimization of Natural Gas Pipeline Dynamics
Authors: Zlotnik Anatoly , Dyachenko Sergey , Backhaus Scott , Chertkov Michael
Published: January 2016

We derive a reduced control system model for the dynamics of compressible gas flow through a pipeline subject to distributed time-varying injections, withdrawals, and control actions of compressors. The gas dynamics PDE equations are simplified using lumped elements to a nonlinear ODE system with matrix coefficients. We verify that low-order integration of this ODE system with adaptive time-stepping is computationally consistent with solution of the PDE system using a split-step characteristic scheme on a regular space-time grid for a realistic pipeline model. Furthermore, the reduced model is tractable for use as the dynamic constraints of the optimal control problem of minimizing compression costs given transient withdrawals and gas pressure constraints. We discretize this problem as a finite nonlinear program using a pseudospectral collocation scheme, which we solve to obtain a polynomial approximation of the optimal transient compression controls. The method is applied to an example involving the Williams-Transco pipeline.
Robust Gain-Scheduling Output Feedback Control of State-Delayed LFT Systems Using Dynamic IQCs
Authors: Yuan Chengzhi , Wu Fen , Duan Chang
Published: January 2016

This paper is concerned with the robust gain-scheduling output feedback control problem for a class of linear parameter-varying systems with time-varying state delay. The controlled plant under consideration is described as a linear fractional transformation (LFT) model of scheduling parameters. Dynamic integral quadratics (IQCs) are employed to characterize the input-output behavior of the state-delay nonlinearity. The robust stability and the L2-gain performance are first analyzed using quadratic Lyapunov function. Then, the design of dynamic output-feedback controllers robust against the plant state-delay nonlinearity and gain-scheduled by parameters is examined. The synthesis conditions of such robust gain-scheduling controllers are formulated in terms of linear matrix inequalities (LMIs) plus a line search, which can be solved effectively using existing algorithms. A numerical example has been used to demonstrate the effectiveness and advantages of the proposed approach.
Optimal Impedance Control of an Upper Limb Stroke Rehabilitation Robot
Authors: Ghannadi Borna , McPhee John
Published: January 2016

There is an increasing prevalence of stroke, spinal cord and brain injuries worldwide. Robotics are becoming a popular form of rehabilitation, but their effectiveness is yet to be proven. Recent motor learning theories motivate us to improve the control algorithms of these robots. This work proposes an optimal impedance control (i.e., a linear quadratic regulator mapped from the operational space) to control a 2 degree of freedom (DOF) upper extremity stroke rehabilitation robot. We used an integrated model of the robot and human (a 2 DOF musculoskeletal arm model) to develop and fine-tune the controller.
An Adaptive Robust Control for Hard Rock Tunnel Boring Machine Cutterhead Driving System
Authors: Shao Chengjun , Liao Jianfeng , Li Xiuliang , Su Hongye
Published: January 2016

The cutterhead driving system of tunnel boring machine is one of the key components for rock cutting and excavation. In this paper, a generalized nonlinear time-varying dynamic model is established for the hard rock TBM cutterhead driving system. Parametric uncertainties and nonlinearities and unknown disturbances exist in the dynamic model. An adaptive robust control strategy is proposed to compensate the uncertainties and nonlinearities to achieve precise cutterhead rotation speed control. In order to simulate the comprehensive performances of adaptive robust control controller, three different kinds of external force disturbances are added in this model. Compared to the traditional PID, ARC can effectively handle the different kinds of external force disturbances with sufficient small tracking errors.
A Diagnostic Scheme for Detection, Isolation and Estimation of Electrochemical Faults in Lithium-Ion Cells
Authors: Dey Satadru , Ayalew Beshah
Published: January 2016

Improvement of the safety and reliability of the Lithium-ion (Li-ion) battery operation is one of the key tasks for advanced Battery Management Systems (BMSs). It is critical for BMSs to be able to diagnose battery electrochemical faults that can potentially lead to catastrophic failures. In this paper, an observer-based fault diagnosis scheme is presented that can detect, isolate and estimate some internal electrochemical faults. The scheme uses a reduced-order electrochemical-thermal model for a Li-ion battery cell. The paper first presents a modeling framework where the electrochemical faults are modeled as parametric faults. Then, multiple sliding mode observers are incorporated in the diagnostic scheme. The design and selection of the observer gains as well as the convergence of the observers are verified theoretically via Lyapunov’s direct method. Finally, the performance of the observer-based diagnostic scheme is illustrated via simulation studies.
Sliding Mode Control for Heart Rate Regulation of Electric Bicycle Riders
Authors: Meyer Daniel , Zhang Wenlong , Tomizuka Masayoshi
Published: January 2016

In this paper a new controller for electric bicycles is proposed to maintain a desired heart rate level and improve the riding experience of cyclists. The controller achieves this by adequately adjusting the motor assistance without affecting the cycling velocity. First, a human heart rate model is fitted to experimental data to model the heart rate response of cyclists during different exercises. Then, a sliding mode controller is designed to keep the human heart rate at a predefined level. Furthermore, a feedforward controller is introduced into the system to improve both the tracking performance and riding experience. The feedforward controller consists of an inverse human heart rate response model, which estimates the necessary rider torque for a desired heart rate level. The controller is implemented with a commercial electric bicycle. Simulation and experimental results are presented to assess the validity of the controller. Whereas the sliding mode controller itself achieves good tracking performance, the sliding mode control combined with the feedforward control additionally reduces the maximal exerted rider torque and improves the riding experience.
A Detection and Warning System for Unintended Acceleration
Authors: Yu Hongtao , Langari Reza
Published: January 2016

This paper presents a data-driven method to detect vehicle problems related to unintended acceleration (UA). A diagnostic system is formulated by analyzing several specific vehicle events such as acceleration peaks and generating corresponding mathematical models. The diagnostic algorithm was implemented in the Simulink/dSpace environment for validation. Major factors that affect vehicles’ acceleration (e.g., changes of road grades and gear shifting) were included in the simulation. UA errors were added randomly when human drivers drove virtual cars. The simulation results show that the algorithm succeeds in detecting abnormal acceleration.
Smartphone-Based Wheel Imbalance Detection
Authors: Siegel Joshua E. , Bhattacharyya Rahul , Sarma Sanjay , Deshpande Ajay
Published: January 2016

Onboard sensors in smartphones present new opportunities for vehicular sensing. In this paper, we explore a novel application of fault detection in wheels, tires and related suspension components in vehicles. We present a technique for in-situ wheel imbalance detection using accelerometer data obtained from a smartphone mounted on the dashboard of a vehicle having balanced and imbalanced wheel conditions. The lack of observable distinguishing features in a Fourier Transform (FT) of the accelerometer data necessitates the use of supervised machine learning techniques for imbalance detection. We demonstrate that a classification tree model built using Fourier feature data achieves 79% classification accuracy on test data. We further demonstrate that a Principal Component Analysis (PCA) transformation of the Fourier features helps uncover a unique observable excitation frequency for imbalance detection. We show that a classification tree model trained on randomized PCA features achieves greater than 90% accuracy on test data. Results demonstrate that the presence or absence of wheel imbalance can be accurately detected on at least two vehicles of different make and model. Sensitivity of the technique to different road and traffic conditions is examined. Future research directions are also discussed.
Torque Estimation in a Wrist Rehabilitation Robot Using a Nonlinear Disturbance Observer
Authors: Saadatzi Mohammadhossein , Long David C. , Celik Ozkan
Published: January 2016

In this paper, we present implementation of a nonlinear disturbance observer algorithm to estimate disturbance torques on a wrist rehabilitation robot. The ultimate goal is to enable accurate estimation of user interaction torques without force/torque sensors. A dynamic model of the Wrist Gimbal two degree-of-freedom forearm and wrist exoskeleton is developed. A nonlinear disturbance observer (NDO) algorithm that incorporates the robot dynamics is implemented. Friction models for both joints of the robot are identified. The robot dynamic model and the accuracy of the disturbance torque estimations are experimentally verified under closed-loop trajectory tracking scenarios.
Model-Free Approaches Applied to the Control of Nonlinear Systems: A Brief Survey With Special Attention to Intelligent PID Iterative Learning Control
Authors: Madadi Elmira , Söffker Dirk
Published: January 2016

Model-based control is one of the popular solutions for designing a controller used to control nonlinear systems. However, the difficulty of obtaining an accurate model is a challenge for control designers. For this reason model-free control (MFC) methods are attractive. This contribution gives an overview on different types of model-free control. It includes an investigation about model-free techniques applied to nonlinear systems. In detail the iPID iterative learning-based method is expressed more detailed. Simulation results also illustrate a successful application and performance of the proposed method.
Trajectory Tracking of a Pendulum-Driven Spherical Robot
Authors: Hogan François Robert , Forbes James Richard
Published: January 2016

In this paper, a controller is designed to achieve tracking of a pendulum-driven spherical robot about a desired trajectory in the presence of model uncertainty and external disturbances. A methodology is proposed to design a feedforward controller for the spherical robot by approximating the desired trajectory using circles as basis functions. A linear state-feedback controller is used to drive the perturbations from the desired trajectory to zero. Numerical simulations show that the controller realizes tracking of the desired trajectory with perturbed initial conditions.
Distributed Flow Sensing Using Bayesian Estimation for a Flexible Fish Robot
Authors: Zhang Feitian , Lagor Francis D. , Yeo Derrick , Washington Patrick , Paley Derek A.
Published: January 2016

Flexibility plays an important role in fish behaviors by enabling high maneuverability for predator avoidance and swimming in turbulence. In this paper, we present a novel, flexible fish robot equipped with distributed pressure sensors for flow sensing. The body of the robot is made of a soft, hyperelastic material that provides flexibility. The fish robot features a Joukowski-foil shape conducive to modeling the fluid analytically. A quasisteady potential-flow model is adopted for real-time flow estimation, whereas a discrete-time vortex-shedding flow model is used for higher-fidelity simulation. The dynamics for the flexible fish robot are presented, and a reduced model for one-dimensional swimming is derived. A recursive Bayesian filter assimilates pressure measurements for estimating the flow speed, angle of attack, and foil camber. Simulation and experimental results are presented to show the effectiveness of the flow estimation algorithm.
Robust Nonlinear Model Predictive Control for Infrared Drying of Automotive Coatings
Authors: Cao Xiaoqing , Ayalew Beshah
Published: January 2016

In this paper, a scheme for estimation and control of moisture content in infrared (IR) drying of paints/coatings is proposed. To deal with the infinite-dimensional nature of the process model associated with the moisture diffusion in the coating film, POD-Galerkin method is first applied for model reduction. Then, an unscented Kalman filter (UKF) is devised for distributed moisture content estimation and nonlinear model predictive control (NMPC) system is designed for tracking a desired average moisture content profile with optimized energy needs. To enhance the control performance in the presence of potential modeling uncertainties, a robust design is also included in the proposed NMPC scheme. The effectiveness of this approach is demonstrated via simulated applications to IR drying of automotive waterborne coatings.
Juggler System: Hybrid Model and Implementation
Authors: Jiménez-Leudo Santiago , Quijano Nicanor , Rodríguez Carlos F.
Published: January 2016

Several juggling systems have been developed in order to control the dynamics of a bouncing element. This system is useful to show the behavior of elements due to impacts, as well as to have control of the trajectory followed by them based on physical principles. In this article, the description of the physical implementation of a juggler system is presented, including its movement control to achieve a specific objective. A hybrid model to analyze and predict the behavior of both the platform and the ball is studied and implemented. Finally, a multi-agent implementation is proposed to synchronize its movements and show how a group of oscillating systems are able to reach a common work point.
Decoupling Transformations for Linear Systems in the Configuration Space
Authors: Sultan Cornel
Published: January 2016

Recent major breakthroughs have been achieved in providing transformations that completely decouple all second order linear time invariant systems directly in the configuration space. A brief review is presented herein.
A Natural User Interface to Drive a Robotic Fish
Authors: De Bellis Mauro , Phamduy Paul , Porfiri Maurizio
Published: January 2016

Interactive control modes for robotic fish based informal science learning activities have been shown to increase user interest in STEM careers. This study explores the use of natural user interfaces to engage users in an interactive activity and excite them about the possibility of a robotics career. In this work, we propose a novel natural user interface platform for enhancing participant interaction by controlling a robotic fish in a set of tasks. Specifically, we develop and characterize a new platform, which utilizes a Microsoft Kinect and an ad-hoc communication protocol. Preliminary studies are conducted to assess the usability of the platform.
Deployment of a Robotic Fish Platform in Informal Science Learning
Authors: Phamduy Paul , Milne Catherine , Leou Mary , Porfiri Maurizio
Published: January 2016

Interactive robotics-based exhibits for informal science learning are becoming increasingly popular, as they offer the novelty of a robot to visitors and they allow them to reflect on their actions through instant feedback from remote control elements. This study explores the deployment of one such platform featuring a robotic fish at informal science learning events and venues. We examine the usage of three control modes, varying in their degree of interactivity, implemented through an iDevice application for maneuvering a robotic fish. Specifically, we evaluate the time spent by visitors on three control modes of the platform at informal science learning event and venues, and the distribution of the demographics of the users. This preliminary study is conducted to assess the user interest among the control modes.
An Adaptive Nonlinear Differentiable Friction Modeling for Tire-Road Friction Estimation
Authors: Fu Zhi-Jun , Rakheja Subhash , Xie Wen-Fang , Ning Xiao-Bin , Xie Wei-Dong
Published: January 2016

In this paper, a differentiable friction model is proposed to estimate the longitudinal tire-road friction force of vehicle systems. A novel adaptive nonlinear observer-based parameter estimation scheme has been developed to estimate the parameters of friction model, which requires the signals from the existing sensors signals such as wheel rotational speed and vehicle speed. Different from conventional gradient and recursive least square (RLS) methods, the filtered regression parameter estimation error is introduced in the novel adaptive laws, which can guarantee the observer error convergence to zero and the estimated parameter also convergence to their real value. The Lyapunov method is used to prove the stability of the proposed methods. The robustness of the developing method against bounded disturbances is also proved. Simulation results illustrate that the proposed method can realize relatively accurate estimation of the friction with variations in speed and road gradient.
Nonlinear Model Predictive Control of Functional Electrical Stimulation
Authors: Kirsch Nicholas A. , Alibeji Naji A. , Sharma Nitin
Published: January 2016

One of the major limitations of functional electrical stimulation (FES) is the rapid onset of muscle fatigue. Minimizing stimulation is the key to decreasing the adverse effects of muscle fatigue caused by FES. Optimal control can be used to compute the minimum amount of stimulation necessary to produce a desired motion. In this paper, a gradient projection-based model predictive controller is used for an approximate optimal control of a knee extension neuroprosthesis. A control Lyapunov function is used as a terminal cost to ensure stability of the model predictive control.
Sensor Signal Limitations in Wheel Rotational Kinematics Estimation Model
Authors: Paldan Jesse R. , Gray Jeremy P. , Vantsevich Vladimir V.
Published: January 2016

Wheel encoders play an important role in providing information about rotational kinematics of vehicle wheels. The sensor signals are utilized in critical vehicle systems responsible for vehicle safety, traction and braking performance, and stability of motion. This paper starts with an analysis of different types of sensors that have been used in rotational wheel kinematics estimations and controls. The main attention is given to sensor signal limitations related to the accuracy of measurement and response time that are important for agile-to-real-time tire dynamics estimation.

A detailed analysis of the wheel rotational velocity estimation process is presented for a conventional Hall Effect digital sensor. Through an analytical modelling, it is shown that this sensor can limit its accuracy due to an increased time for signal information assembly caused by the number of impulses and transient (unsteady) rotational motion in unstable road conditions.

A new concept of a rotational kinematics sensor is proposed and modeled as a multi-domain mechatronic system that includes new mechanical elements as well as electrical and magnetic components. The sensor concept provides a smooth continuous signal through the full rotational angle of the wheel and precise information about the rotational velocity and its changes in different unstable road conditions. Computational examples of both sensors (digital and proposed) are demonstrated with the use of a quarter-car model moving over a random road profile in stochastic gripping and rolling resistance conditions. A comparison of the two sensors’ accuracy to estimate the rotational velocity of the wheel is done with regard to an “ideal” sensor with a unity transfer function.
ROM of Superharmonic Resonance of Second Order of Electrostatically Actuated MEMS Resonators
Authors: Caruntu Dumitru I. , Reyes Christian
Published: January 2016

This paper deals with the voltage-amplitude response (or voltage response) of superharmonic resonance of second order of MEMS resonator sensors under electrostatic actuation. The system consists of a MEMS flexible cantilever above a parallel ground plate. The AC frequency of actuation is near one fourth the natural frequency. The voltage response of the superharmonic resonance of second order of the structure is investigated using the Reduced Order Model (ROM) method. Effects of voltage and damping voltage response are reported.
Modulation of Nonlinear Hydrodynamic Damping in Finite Amplitude Underwater Oscillations of Flanged Structures
Authors: Ahsan Syed N. , Aureli Matteo
Published: January 2016

In this paper, we study the fluid-structure interaction problem of the harmonic oscillations of a flanged lamina in a quiescent, Newtonian, viscous fluid. Here, the flanges are introduced to elicit specific vortex-structure interactions, with the ultimate goal of modulating the nonlinear hydrodynamic damping experienced by the oscillating structure. The hydrodynamic forcing, incorporating added mass and hydrodynamic damping effects, is evaluated through boundary element method and computational fluid dynamics simulations. This allows to identify a model for the hydrodynamic forces in the form of a complex-valued function of three nondimensional parameters, describing oscillation frequency and amplitude and flange size. We find that the presence of the flanges results into larger fluid entrainment during the lamina oscillation, thus affecting the added mass. Further, we highlight the existence of a minimum in the hydrodynamic damping which is governed by complex dynamics of vortex-structure interaction. This peculiar phenomenon is discussed from physical grounds by analysis of the pertinent hydrodynamic fields. Finally, we propose a tractable form for the hydrodynamic function, to be used in the study of large amplitude underwater flexural vibrations of flanged structures.
Design and Assessment of a High Speed Low Torque Joint Transmission for Use in a Partial Hand, Powered Finger Prosthesis
Authors: Filatov Anton , Celik Ozkan , Weir Richard F.
Published: January 2016

This paper presents the design and assessment results of two types of miniature, high speed, low torque transmissions to be used in a partial hand, powered finger prosthesis. Transmissions enabling torque transfer across varied flexion angles of a finger joint can allow placement of a motor and a gearbox in adjacent phalanges, significantly decreasing space requirements for partial hand prostheses. Bevel gear-based and cable-based transmission designs for a variety of flexion angles are implemented and tested in comparison with a direct cascaded motor and gearbox (benchmark) configuration. The miter-gear transmission provided consistent operation at tested flexion angles, but demonstrated reduced efficiency in comparison with the benchmark configuration. Cable transmission matched efficiency of the benchmark configuration at low flexion angles but lacked mechanical durability at high loads and flexion angles. The designs presented complementary strengths and weaknesses, with the miter-gear design demonstrating better overall mechanical reliability, while the cable transmission excelled in secondary characteristics.
Assist-as-Needed Controllers for Index Finger Module of a Hand Exoskeleton for Rehabilitation
Authors: Agarwal Priyanshu , Fernandez Benito R. , Deshpande Ashish D.
Published: January 2016

We present two types of subject-specific assist-as-needed controllers for the index finger module of a hand exoskeleton designed for rehabilitation after a neuromuscular impairment such as stroke. Learned force-field control is a novel control technique in which a neural-network-based model of the required torques is learned for a specific subject and then used to build a force-field to assist the subject’s finger joint motion. Adaptive assist-as-needed control, on the other hand, estimates the coupled finger-exoskeleton system torque requirement of a subject using radial basis function (RBF) and on-the-fly adapts the RBF magnitudes to provide a feed-forward assistance for improved trajectory tracking. Experiments on the index finger exoskeleton prototype with a healthy subject showed that while the force-field control is non-adaptive and there is less control on the speed of execution of the task, it is safer as it does not apply increased torques if the finger motion is restricted. On the other hand, adaptive assist-as-needed controller adapts to the changing needs of the coupled finger-exoskeleton system and helps in performing the task with a consistent speed, however, applies increased torques in case of restricted motion resulting in potential user discomfort.
Stable Robust Adaptive Impedance Control of a Prosthetic Leg
Authors: Azimi Vahid , Simon Dan , Richter Hanz
Published: January 2016

We propose a nonlinear robust model reference adaptive impedance controller for an active prosthetic leg for transfemoral amputees. We use an adaptive control term to consider the uncertain parameters of the system, and a robust control term so the system trajectories converge to a sliding mode boundary layer and exhibit robustness to variations of ground reaction force (GRF). The boundary layer not only compromises between control chattering and tracking performance, but also bounds the parameter adaptation to prevent unfavorable parameter drift. We also prove the stability of the controller for the robotic system in the case of non-scalar boundary layer trajectories using Lyapunov stability theory and Barbalat’s lemma. The acceleration-free regressor form of the system removes the need to measure the joint accelerations, which would otherwise introduce noise in the system. We use particle swarm optimization (PSO) to optimize the design parameters of the controller and the adaptation law. The PSO cost function is comprised of control signal magnitudes and tracking errors. PSO achieves a 8% improvement in the objective function. Finally, we present simulation results to validate the effectiveness of the controller. We achieve good tracking of joint displacements and velocities for both nominal and perturbed values of the system parameters. Variations of ±30% on the system parameters result in an increase of the cost function by only 3%, which confirms the robustness of the controller.
A New Vibration Controller Design Using Consensus Technique
Authors: Omidi Ehsan , Mahmoodi S. Nima
Published: January 2016

This paper discusses the concept of a new methodology for active vibration control of flexible structures using consensus control of network systems. In the new approach, collocated actuation/sensingpatches communicate with one another through a network with certain directed topology. A virtual leader is assigned to enforce the vibration amplitude at the place of each agent to zero. Since the modal states of the system are not available for the vibration control task, individual optimal observers are designed for each agent first. After describing the controller and examining the stability of the system, controller performance is verified using a clamped-clamped thin aluminum beam. According to the obtained numerical results, the new control approach successfully suppresses the vibration amplitudes, while the consensus design ensures that all agents are synchronized during the performance.
Development of a Miniaturized Autonomous Vehicle: Modification of a 1:18 Scale RC Car for Autonomous Operation
Authors: Iyengar Dwarkesh , Peters Diane L.
Published: January 2016

Autonomous vehicles are a subject of intense research interest, and are being approached by many researchers in different ways. Some of these approaches are based upon pure simulation, while others involve investigations using hardware. One possible approach, which can be useful when investigating how autonomous vehicles might interact, involves the use of physical scaled model vehicles, and the development of an appropriate vehicle is the focus of this paper. For this purpose, a commercially available 1:18 radio controlled car is remodeled and modified. An onboard microcontroller unit (MCU) is used for sensor data acquisition and preliminary signal conditioning as well as actuator control. The sensor array includes a gyroscope/accelerometer, a compass and speed encoder to find the angular and linear position of the car in a local coordinate frame as well as a range finder to detect impending obstacles in the vehicle’s planned path. This information is sent over a serial communication protocol to a Master station via a 2.4 GHz wireless module. The master station consists of a National Instruments (NI) myRIO real-time FPGA module where the local coordinates are used to formulate the position of the car in global coordinates and a user defined control scheme is implemented and the appropriate actuator signal is sent back wirelessly to the MCU on the car. The main purpose of using an independent and offsite control station is to isolate the main processing and increase response speed to changing environmental factors. Furthermore, the myRIO contains the dynamic model of the car which can be modified by linking it to a personal computer station running the LabVIEW graphic user interface (GUI). This adds greater flexibility to the overall system, thus allowing the user to focus on the different control schemes to be implemented through the hardware setup. This setup will be replicated for more cars, set in an urban traffic environment, and the interactions between the cars can then be studied and optimized.
Fuel Efficient Control Strategies for Connected Hybrid Electric Vehicles in Urban Roads
Authors: Lin Runing , HomChaudhuri Baisravan , Pisu Pierluigi
Published: January 2016

This paper presents a fuel efficient control strategy for a group of connected hybrid electric vehicles (HEVs) in urban road conditions. A hierarchical control architecture is proposed in this paper where the higher level controller is considered to be a part of the transportation infrastructure while the lower level controllers are considered to be present in every HEV. The higher level controller uses model predictive control strategy to evaluate the energy efficient velocity profiles for every vehicle for a given horizon. Each lower level controller then tracks its velocity profile (obtained from the higher level controller) in a fuel efficient fashion using equivalent consumption minimization strategy (ECMS). In this paper, the vehicles are modeled in Autonomie software and the simulation results provided in the paper shows the effectiveness of our proposed control architecture.
Feedback-Based Temperature and Irradiation Estimation for Photovoltaic Systems
Authors: Docimo Donald J. , Ghanaatpishe Mohammad , Mamun Abdullah-Al
Published: January 2016

This paper develops two algorithms for estimating photovoltaic (PV) module temperature and effective irradiation level. The efficiency of PV systems depends on the module temperature, and both temperature and irradiation determine the power output of the system. Estimating these two quantities allows for improved state-based control methods while eliminating the need of additional sensors. Thermal models and irradiation estimators have been developed in the literature, but none incorporate feedback for estimation. This paper outlines two feedback-based observers for temperature and irradiation, each with a different irradiation model, and validates the proposed observer techniques through simulation.
Effective Tuning of Cascaded Control Loops for Nonlinear HVAC Systems
Authors: Price Christopher R. , Rasmussen Bryan P.
Published: January 2016

Residential and commercial buildings are large consumers of energy in the United States with Heating, Ventilation, and Air-Conditioning (HVAC) systems representing a significant portion of total use. These systems control aspects such as humidity and room air temperature to ensure building occupant comfort. Control of HVAC units presents unique challenges due to large nonlinearities heavily dependent on operating conditions. Static linear controllers are unable to counteract such nonlinearities resulting in sustained oscillations known as hunting behavior. Previous research has shown the ability of cascaded architectures to compensate for HVAC nonlinearities and improve overall system performance without the need for detailed dynamic models. To aid the implementation of cascaded loops on real building systems, analysis of the effects of inner loop gain are presented and three outer loop tuning cases are identified. A simulation case study of an air handling unit demonstrates the simplicity of the procedure and compares it with optimally tuned gains.
Complete Dynamic Modelling of Flexible Joint Robots
Authors: Zhao Yu , Wang Cong , Yu Xiaowen , Tomizuka Masayoshi
Published: January 2016

Joint flexibility is common in industrial robots that have geared joints. In order to design a precision motion controller that compensates the effects of joint elasticity, an accurate dynamic model of flexible joint robots is required. The models that are commonly used ignore the gyroscopic interactions between the motors and links. In order to evaluate the influence of the ignored gyroscopic interaction, a complete dynamic model for flexible joint robots is derived in this paper. It is shown that when to realize high accuracy for high velocity trajectory tracking, the motor inertia is non-negligible compared to link inertia, and that the neglected interaction terms must be taken into account.
On the System-Theoretic Passivity Properties of a Hill Muscle Model
Authors: Richter Hanz , van den Bogert Antonie J.
Published: January 2016

The paper describes passivity-related input-output properties of a human muscle and tendon system given by a Hill type dynamic model. For a model having muscle contraction velocity as the input and force as the output, it is shown that the system is passive during the concentric phase. Also, it is shown that a negative strict passivity margin exists for the eccentric phase if the length and lengthening velocity of the contractile element are assumed bounded. Estimates of this margin are given by means of two alternative formulas. Further, it is shown that the mapping from contraction velocity to deviation from equilibrium force is passive in both concentric and eccentric phases. The paper discusses how these findings and the passivity theorem can be used to design controllers for a machine coupled to the muscle model by feedback interconnection. The simple case of a proportional-derivative force feedback regulator is considered as an example. A simulation example is given where the transient response of the coupled system crosses the eccentric region.
An Analytical Approach for Predicting Power Generation of Impulsively-Excited Bistable Vibration Energy Harvesters
Authors: Harne R. L. , Zhang Chunlin , Li Bing , Wang K. W.
Published: January 2016

The high sensitivity to impulse-type events previously uncovered for bistable oscillators has motivated recent experimental and numerical studies on the power generation performance of bistable vibration energy harvesters. To lead to an effective and efficient predictive tool and design guide, this research develops a new analytical approach to estimate the vibration response decay and power generation of a bistable energy harvester when excited by an impulse. Enabling the prediction of time-varying snap-through dynamics, this new approach greatly extends the capabilities of the current averaging method when employed with the Jacobian elliptic functions. Comparison with values determined by the direct simulation of the governing equations shows that the analytically predicted average generated power is very accurate for a wide range of impulse strengths and load resistances. The analytical approach represents a great leap forward in the ever-expanding understanding of bistable vibration energy harvesters as implements to effectively capture and convert a wide range of excitation energies.
Online Prognostics for Fuel Thermal Management System
Authors: DeSimio Martin P. , Hencey Brandon M. , Parry Adam C.
Published: January 2016

Modern tactical aircraft subsystems face challenging weight and volume limitations. In addition, power and thermal subsystems have grown increasingly flight critical with each successive generation. Consequently, next generation power and thermal systems must reliably operate under narrower margins to enable electrically and thermally demanding capabilities, such as directed energy weapons. The ability to narrow these margins is ultimately limited by the ability to guarantee mission objectives despite variations and uncertainty in power and thermal system performance. This paper demonstrates online prognostic methods applied to a fuel thermal management system. Furthermore, this paper highlights the need for future research to quantify the effects on mission objectives caused by discrepancies between nominal and actual conditions for aircraft designs based on models of highly integrated systems.
Assessment of the Vehicle Level Impact for a SOFC Integrated With the Power and Thermal Management System of an Air Vehicle
Authors: Roberts Rory A. , Wolff Mitch , Nuzum Sean , Donovan Adam
Published: January 2016

The demand for electrical power onboard aerospace vehicles continues to grow at an accelerating pace. Accompanied with the electrical power is the increase in thermal demands for removing the low quality waste heat from the electrical components and advanced electronics. The increase in thermal demands onboard an aircraft dramatically impact the capability and performance of the air vehicle due to the low coefficients of performance (COP) of aerospace refrigeration systems. The low COP means the system requires a significant amount of work to lift the thermal waste from the aircraft subsystems. This leads to significant demands on the propulsion system and the power and thermal management systems creating a cycle of diminishing returns, which leads to inefficiency and limited capability of future air vehicles. Alternative components and configurations have the potential to increase the efficiency of the power and thermal management system reducing the overall negative impact on air vehicles’ efficiency and capabilities. A solid oxide fuel cell (SOFC) integrated with the power and thermal management system has been investigated. The vehicle level impact of this novel configuration has been assessed along with the dynamic behavior of the SOFC when integrated into these systems. The results provide insight into the advantages and disadvantages of the proposed system.
Automated Robust Path Following Control Based on Calculation of Lateral Deviation and Yaw Angle Error
Authors: Emirler Mümin Tolga , Wang Haoan , Aksun Güvenç Bilin , Güvenç Levent
Published: January 2016

Automated driving vehicles are expected to be ready for series production by 2020. An important component of automated driving technologies is controlled path following under longitudinal speed control. In this paper, a robust path following controller design based on lateral deviation and yaw angle error determination of the vehicle is proposed. The constrained least square method is used for obtaining continuity and smoothness of the segment boundaries of the digital trajectory map to be followed. The lateral deviation and yaw angle error are calculated by comparing the generated digital map trajectory and the vehicle position. The parameter space approach is used in the design stage of the controller considering D-stability requirements. The solution regions of the controller are plotted in three dimensional parameter space. The designed controller is tested with simulations on a path chosen from the Ohio State University campus.
Comparative Evaluation of Control-Oriented Zone Temperature Prediction Modeling Strategies in Buildings
Authors: Chinde Venkatesh , Heylmun Jeffrey C. , Kohl Adam , Jiang Zhanhong , Sarkar Soumik , Kelkar Atul
Published: January 2016

Predictive modeling of zone environment plays a critical role in developing and deploying advanced performance monitoring and control strategies for energy usage minimization in buildings while maintaining occupant comfort. The task remains extremely challenging, as buildings are fundamentally complex systems with large uncertainties stemming from weather, occupants, and building dynamics. Over the past few years, purely data-driven various control-oriented modeling techniques have been proposed to address different requirements, such as prediction accuracy, flexibility, computation and memory complexity. In this context, this paper presents a comparative evaluation among representative methods of different classes of models, such as first principles driven (e.g., lumped parameter autoregressive models using simple physical relationships), data-driven (e.g., artificial neural networks, Gaussian processes) and hybrid (e.g., semi-parametric). Apart from quantitative metrics described above, various qualitative aspects such as cost of commissioning, robustness and adaptability are discussed as well. Real data from Iowa Energy Center’s Energy Resource Station (ERS) test bed is used as the basis of evaluation presented here.
Learning Contracting Nonlinear Dynamics From Human Demonstration for Robot Motion Planning
Authors: Ravichandar Harish , Dani Ashwin
Published: January 2016

In this paper, we present an algorithm to learn the dynamics of human arm motion from the data collected from human actions. Learning the motion plans from human demonstrations is essential in making robot programming possible by nonexpert programmers as well as realizing human-robot collaboration. The highly complex human reaching motion is generated by a stable closed-loop dynamical system. To capture the complexity a neural network (NN) is used to represent the dynamics of the human motion states. The trajectories of arm generated by humans for reaching to a place are contracting towards the goal location from various initial conditions with built in obstacle avoidance. To take into consideration the contracting nature of the human motion dynamics the unknown motion model is learned using a NN subject to contraction analysis constraints. To learn the NN parameters an optimization problem is formulated by relaxing the non-convex contraction constraints to Linear matrix inequality (LMI) constraints. Sequential Quadratic Programming (SQP) is used to solve the optimization problem subject to the LMI constraints. For obstacle avoidance a negative gradient of the repulsive potential function is added to the learned contracting NN model. Experiments are conducted on Baxter robot platform to show that the robot can generate reaching paths from the contracting NN dynamics learned from human demonstrated data recorded using Microsoft Kinect sensor. The algorithm is able to adapt to situations for which the demonstrations are not available, e.g., an obstacle placed in the path.
A Control Theoretic Framework for Optimally Locating Passive Vibration Isolators to Minimize Residual Vibration
Authors: Ghasemi Amir H. , Lee Jihyun , Okwudire Chinedum E.
Published: January 2016

This paper investigates the problem of optimally locating passive vibration isolators to minimize residual vibration caused by exogenous disturbance forces. The stiffness and damping properties of the isolators are assumed to be known and the task is to determine the isolator locations, which are nonlinearly related to system states. This paper proposes an approach for reformulating the nonlinear isolator placement problem as a LTI control problem by linking the control forces to measured outputs using a feedforward term. Accordingly, the isolator locations show up as a static output feedback gain matrix which is optimized for residual vibration reduction using standard H∞ optimal control methods. Simulations and experiments on SISO and MIMO case studies are used to demonstrate the merits of the proposed approach. Even though presented in the specific context of ultra-precision manufacturing machines, the proposed method is applicable to the optimal design of other passive systems with nonlinear relationships between design variables and system states.
Dynamic Modeling of Robotic Fish Caudal Fin With Electrorheological Fluid-Enabled Tunable Stiffness
Authors: Bazaz Behbahani Sanaz , Tan Xiaobo
Published: January 2016

In this study, we investigate the modeling framework for a robotic fish actuated by a flexible caudal fin, which is filled with electrorheological (ER) fluid and thus enables tunable stiffness. This feature can be used in optimizing the robotic fish speed or maneuverability in different operating regimes. The robotic fish is assumed to be anchored and the flexible tail undergoes undulation activated by a servomotor at the base. Lighthill’s large-amplitude elongated-body theory is used to calculate the hydrodynamic force on the caudal fin, and Hamilton’s principle is used to derive the dynamic equations of motion of the caudal fin. The dynamic equations are then discritized using the finite element method, to obtain an approximate numerical solution. In particular, simulation is conducted to understand the influence of the applied electric field on the stiffness and thrust performance of the caudal fin.
Integrating Structure and Controller Design to Mechanical Systems via Decentralized Control Techniques
Authors: Liu Yilun , Zuo Lei
Published: January 2016

The overall performance of the mechanical system can be significantly improved by concurrently optimizing the plant and the controller. This paper proposes a new integrated design method via decentralized control techniques to concurrently optimize the structure and the controller, which aims at minimizing the system H2 norm from the disturbance to the system cost. The integrated design problems have been formulated in the cases of a full state feedback controller and a full order output feedback controller respectively. Inspired by noticing that the control techniques are capable of optimizing both the parameters of passive springs and dampers and the controller for the mechanical system, we extend the current LTI control system to a more general framework suitable for the integrated design needs, where the structure design is treated as the passive control optimization tackled by decentralized control techniques with static output feedback, while the active controller is optimized by solving the modified Riccati equations. With the extended system framework, we transfer the original non-convex integrated optimization problem to an unconstrained optimization problem by introducing Lagrange multipliers and a Lagrange function. The gradient-based optimization method is employed to effectively find the optimality solution of the integrated design. Two design examples including an active-passive vehicle suspension system and an active-passive Tuned Mass Damper (TMD) system are designed by the proposed integrated design method. The improvement of the overall system performance due to the integrated design is also presented in comparison with the conventional design methods.
An Optimal Energy Management System for Electric Vehicles Hybridized With Supercapacitor
Authors: Golchoubian Parisa , Azad Nasser L.
Published: January 2016

In this study, the potential merits of integrating a supercapacitor into an electric vehicle (EV), namely a Toyota RAV4 EV, is investigated. In particular, the impacts of energy management system (EMS) with a buffer scheme and a dynamic programming (DP)-based control law on the vehicle performance characteristics are examined and compared to the vehicle with no supercapacitor in use. While the simulation results show improvements in the vehicle’s driving range and heat loss for the both considered EMSs, the DP-based controller significantly outperforms the buffer policy. The investigations also demonstrate promising results regarding the use of supercapacitors in EVs, intriguing interest for further studies on online control strategies for these systems.