bluuebunny/crossref_metadata_2025 huggingface dataset:
Individually Controllable Magnetic Cilia: Mixing Application
Authors: Banka Nathan , Ng Yau Luen , Devasia Santosh
Published: February 2017

This paper introduces a new design for individually controlled magnetic artificial cilia for use in fluid devices and specifically intended to improve the mixing in DNA microarray experiments. The design has been implemented using a low-cost prototype that can be fabricated using polydimethylsiloxane (PDMS) and off-the-shelf parts and achieves large cilium deflections (59% of the cilium length). The device's performance is measured via a series of mixing experiments using different actuation patterns inspired by the blinking vortex theory. The experimental results, quantified using the relative standard deviation of the color when mixing two colored inks, show that exploiting the individual control leads to faster mixing (38% reduction in mixing time) than when operating the device in a simultaneous-actuation mode with the same average cilium beat frequency. Furthermore, the experimental results show an optimal beating pattern that minimizes the mixing time. The existence and character of this optimum is predicted by simulations using a blinking-vortex approach for 2D ideal flow, suggesting that the blinking-vortex model can be used to predict the effect of parameter variation on the experimental system.
Analysis of Impact Loads on a Self-Elevating Unit During Jacking Operation
Authors: Ringsberg Jonas W. , Daun Viktor , Olsson Fredrik
Published: February 2017

A method is presented that enables the analysis of weather window assessments for the installation and retrieval phases of a self-elevating unit (SEU). The method takes site-specific parameters, defined as soil type and water depth, into account in addition to vessel-specific and environmental parameters. The inclusion of site-specific parameters is the novel contribution compared to assessment methodologies used today. A simulation model is presented that incorporates a coupled nonlinear time-domain analysis of vessel motion and soil–structure interaction. Soil deformation behavior during impact is described by resistance curves based on a bearing capacity theory. A structural evaluation criterion against which impact forces are compared is used for weather window assessments. The simulation model is applied on a case study utilizing different soil types to study impact forces and the capacity of the structure for withstanding such impacts and eventually performing a weather window assessment. The results show that the jacking operation can be divided into two phases when it comes to loads on the spudcan: a phase dominated by vertical forces followed by a phase dominated by horizontal forces. It is found that including soil deformation behavior is of paramount importance to the magnitude of the resulting impact forces and that class-recommended practice does indeed produce rather large force estimates. Thus, assessments where site-specific parameters are incorporated could definitely increase the operable weather window for SEUs, and, consequently, increase the economic competitiveness of, for example, the offshore wind industry.
Multi-Body Dynamics Model of a Tracked Vehicle Using a Towing Winch for Optimal Mobility Control and Terrain Identification
Authors: Cook Joshua T. , Ray Laura , Lever James
Published: February 2017

This paper presents a generalized, multi-body dynamics model for a tracked vehicle equipped with a winch for towing operations. The modeling approach couples existing formulations in the literature for the powertrain components and the vehicle-terrain interaction to provide a comprehensive model that captures the salient features of terrain trafficability. This coupling is essential for making realistic predictions of the vehicle’s mobility capabilities due to the power-load relationship at the engine output. Simulation results are presented jointly with experimental data to validate these dynamics under conditions where no action is taken by the winch. Extended modeling includes dynamics of the hydraulic system that powers the winch so that the limitation of the winch as an actuator and the load it puts on the engine are realized. A second set of simulation results show that for a set of open loop control actions by the winch, the vehicle is able to maintain its mobility in low traction terrain by paying the towed load in and out.
Nonlinear Data Classification and Applications to Vehicle Calibration Identification
Authors: Wang Jing , Wang Yan , Filev Dimitar , Llusho Lirjon
Published: February 2017

In this paper, we consider the general problem of data classification, and focus on the development of suitable approaches for automotive calibration applications. Specifically, we propose two methods for nonlinear data classification: the first one is to find the smallest piecewise linear (PWL) region for a given data set and the second one is to construct piecewise quadratic (PWQ) boundary to separate two data sets . In both methods, the construction of the boundary curve is formulated as convex optimization problems that can be solved efficiently. Our approaches can incorporate prior information about data distribution and allow fixed structure of the decision boundary from different data sets with similar generating sources. We demonstrate the efficiency and effectiveness of the approaches with an application to calibration identification of vehicle rollover detection algorithm.
Nonparametric Tool Path Compensation for Machining Flexible Parts
Authors: Hatakeyama Waku , Wang Cong , Lu Lu
Published: February 2017

This paper discusses the compensation of tool paths for machining flexible parts. Despite various research published on the topic, machining in practice nowadays remains limited to tool path planning based on only the geometric models of the parts and tools. This is mainly because that tool path compensation methods usually require accurate physical information of the systems and rely on analytical or finite element simulations, which are often not available to the end-users. In regards to this problem, this paper presents data-oriented nonparametric learning methods that require solely the geometric measurements of the trial machined contour(s). The physical parameters of the parts and tools as well as simulations of the machining process are not required. Two algorithms are developed based on Gaussian Process Regression and Artificial Neural Network respectively. Experimental tests are conducted. A plan of further improving the results using an auxiliary real-time vision sensor is also discussed.
Design for Ease of Control and Estimation
Authors: Ulsoy A. Galip
Published: February 2017

Traditionally, a dynamic system is first designed then its controller is designed in a sequential process, which offers many organizational and computational advantages. However, this sequential design approach may not lead to system optimality compared to the combined design, or co-design, of the dynamic system and its controller. It has been proposed that a control proxy function (CPF) be used in the first step of this sequential design process to achieve, or approach, system-optimality. This paper considers the use of a CPF based on controllability and observability Gramians and a balanced realization to ensure the design of the dynamic system for both ease of control and estimation. The proposed approach is illustrated using an example of linear quadratic design for combined passive and active vibration control.
Wireless Temperature Sensing Using Permanent Magnets for Multiple Points Undergoing Repeatable Motions
Authors: Chen Yi , Guba Oksana , Brooks Carlton F. , Roberts Christine C. , van Bloemen Waanders Bart G. , Nemer Martin B.
Published: February 2017

Temperature monitoring is essential in automation, mechatronics, robotics and other dynamic systems. Wireless methods which can sense multiple temperatures at the same time without the use of cables or slip-rings can enable many new applications. A novel method utilizing small permanent magnets is presented for wirelessly measuring the temperature of multiple points moving in repeatable motions. The technique utilizes linear least squares inversion to separate the magnetic field contributions of each magnet as it changes temperature. The experimental setup and calibration methods are discussed. Initial experiments show that temperatures from 5 to 50 °C can be accurately tracked for three neodymium iron boron magnets in a stationary configuration and while traversing in arbitrary, repeatable trajectories. This work presents a new sensing capability that can be extended to tracking multiple temperatures inside opaque vessels, on rotating bearings, within batteries, or at the tip of complex end-effectors.
Analysis of an Error Integral Driven MIMO SM Regulator for LTI Systems
Authors: Yunt Kerim
Published: February 2017

In this work an error-integral-driven sliding mode controller (EID-SMC) for multi-input multi-output (MIMO) minimum phase linear time-invariant (LTI) systems with feedthrough controls and output disturbance is analyzed. Though the sliding variable remains in the vicinity of the sliding surface without reaching it, it is shown that the steady-state error vanishes exponentially asymptotically within the boundary layer even if parameter uncertainty and unmatched input/output disturbances exist. The pole-placement is accomplished indirectly by an iterative optimization routine by considering limits on controls and state contrary to the existing practice in SMC where either direct pole placement or quadratic norm optimality of a performance is used. For the proposed controller framework the Luenberger observer is presented.
A Model for Citizen Scientist Contribution in an Image Tagging Task
Authors: Laut Jeffrey , Cappa Francesco , Nov Oded , Porfiri Maurizio
Published: February 2017

Citizen science projects are becoming increasingly popular, yet they typically rely on only a small portion of users for the majority of contribution. In this paper, we propose a model for citizen scientist contribution in an online image tagging task. The model describes participant contribution in response to the performance of a virtual peer, the behavior of which can be controlled by the experimenter. Experimental trials where the virtual peer behaves independent of the participant are used to calibrate the model. The model’s ability to predict participant performance is then verified in a closed-loop condition, where the behavior of the virtual peer is explicitly dependant on the performance of the participant. We foresee this model being a useful tool in the design of web-based citizen science projects, where the behavior of a virtual peer can be used to modulate the performance of contributors in an effort to increase overall levels of contribution.
Disturbance Estimation for Magnetic Piston Position Applications
Authors: Madson Ryan , Rajamani Rajesh
Published: February 2017

The magnetic field of a moving piston can be used for real-time estimation of its position. Piston position estimation is useful for a number of automation and performance improvement applications in hydraulic actuators, pneumatic cylinders, and I.C. engines. A significant challenge to magnetic field based position estimation comes from disturbances due to unexpected ferromagnetic objects coming close to the sensors.

This paper develops a new disturbance estimation method based on modeling the magnetic disturbance as a dipole with unknown location and magnitude. A Truncated Interval Unscented Kalman Filter (TIUKF) is used to estimate all the parameters of this unknown dipole. Experimental data from a pneumatic actuator is used to verify the performance of the developed estimator. Experimental results show that the developed estimator is significantly superior to a linear magnetic field model based disturbance estimator.
A Coordinated Boost Control in a Twincharged Spark Ignition Engine With High External Dilution
Authors: Nazari Shima , Stefanopoulou Anna , Kiwan Rani , Tsourapas Vasilios
Published: February 2017

This paper proposes a novel master-slave control strategy for coordination of throttle, wastegate and supercharger actuators in an electrically twincharged engine in order to guarantee efficient boost control during transients, while at steady state a throttle-wastegate coordination provides minimum engine backpressure hence engine efficiency elevation. The benefits and challenges associated with Low Pressure Exhaust Gas Recirculation (LP-EGR) in a baseline turbocharged engine, including improved engine efficiency, mainly due to better combustion phasing, and sluggish engine response to a torque demand due to slowed down air path dynamics were studied and quantified in [1]. Hence in this paper an electrical Eaton TVS roots type supercharger at high pressure side of the turbocharger compressor (TC compressor) is added to the baseline turbocharged engine and the performance of the proposed controller in the presence of LP-EGR, which is a more demanding condition, is evaluated and compared to the turbocharged engine. One dimensional (1D) crankangle resolved engine simulations show that the proposed master-slave control strategy can effectively improve the transient response of the twincharged engine, making it comparable to naturally aspirated engines, while the consumed electrical energy during transients can be recovered from the decreased fuel consumption due to LP-EGR conditions at steady state in approximately 1 second. Finally, a simple controller is developed to bypass the TC compressor and maximize the engine feeding charge during the transients in order to avoid TC compressor choking and achieve faster response.
Attitude Estimation With a 9-Axis MEMS Based Motion Tracking Sensor
Authors: Wang Yan , Rajamani Rajesh
Published: February 2017

This paper discusses the development of the attitude estimation algorithm for a MEMS based 9-axis motion tracking sensor, which includes a tri-axis accelerometer, a tri-axis gyroscope and a tri-axis magnetometer. The comparison between the Euler angles and the direction cosine matrix (DCM) based approach is presented to illustrate the advantage of DCM. It will be shown that the kinematic model for DCM can be transformed into a linear time-varying state space form, which greatly simplifies the development of the estimation algorithm. Different from the existing estimation algorithms, which incorporate a nonlinear kinematic model and the nonlinear Kalman filter, such as extended Kalman filter (EKF) or unscented Kalman filter (UKF), the non-linearity in the kinematic model is not the trouble maker anymore. Hence, global convergence can always be guaranteed. Finally, the estimation algorithm is demonstrated by using the real measurement data collected from InvenSenses MPU9250, which is one of the most popular 9-axis motion tracking sensors in the market.
A Control Strategy for Eliminating Bouncing in RF MEMS Switches
Authors: Allafi Amer L. , Chahal Premjeet , Mukherjee Ranjan , Khalil Hassan K.
Published: February 2017

RF MEMS switches have many advantages over solid-state switches but their main disadvantage is poor reliability. The reliability problem stems from the impact forces generated at the time of closing of the switch and subsequent bouncing. This paper proposes a feedback control strategy to rapidly close the switch without bouncing. The stiffness of the system is switched between a positive value and a negative value to achieve small rise and setting times with no overshoot. Simulation results are presented to demonstrate the feasibility of the proposed control strategy.
Voltage Response of Superharmonic Resonance of Electrostatically Actuated MEMS Resonator Cantilevers Using the Method of Multiple Scales
Authors: Caruntu Dumitru I. , Reyes Christian
Published: February 2017

This work investigates the voltage response of superharmonic resonance of second order of electrostatically actuated Micro-Electro-Mechanical Systems (MEMS) resonator cantilevers. The results of this work can be used for mass sensors design. The MEMS device consists of MEMS resonator cantilever over a parallel ground plate (electrode) under Alternating Current (AC) voltage. The AC voltage is of frequency near one fourth of the natural frequency of the resonator which leads to the superharmonic resonance of second order. The AC voltage produces an electrostatic force in the category of hard excitations, i.e. for small voltages the resonance is not present while for large voltages resonance occurs and bifurcation points are born. The forces acting on the resonator are electrostatic and damping. The damping force is assumed linear. The Casimir effect and van der Waals effect are negligible for a gap, i.e. the distance between the undeformed resonator and the ground plate, greater than one micrometer and 50 nanometers, respectively, which is the case in this research. The dimensional equation of motion is nondimensionalized by choosing the gap as reference length for deflections, the length of the resonator for the axial coordinate, and reference time based on the characteristics of the structure. The resulting dimensionless equation includes dimensionless parameters (coefficients) such as voltage parameter and damping parameter very important in characterizing the voltage-amplitude response of the structure. The Method of Multiple Scales (MMS) is used to find a solution of the differential equation of motion. MMS transforms the nonlinear partial differential equation of motion into two simpler problems, namely zero-order and first-order. In this work, since the structure is under hard excitations the electrostatic force must be in the zero-order problem. The assumption made in this investigation is that the dimensionless amplitudes are under 0.4 of the gap, and therefore all the terms in the Taylor expansion of the electrostatic force proportional to the deflection or its powers are small enough to be in the first-order problem. This way the zero-order problem solution includes the mode of vibration of the structure, i.e. natural frequency and mode shape, resulting from the homogeneous differential equation, as well as particular solutions due to the nonhomogeneous terms. This solution is then used in the first-order problem to find the voltage-amplitude response of the structure. The influences of frequency and damping on the response are investigated. This work opens the door of using smaller AC frequencies for MEMS resonator sensors.
A Single-Bit Binary Estimator for Use in Control Systems Featuring Serial Communication Channels
Authors: Thomas Josiah R. , Chiu George T. C.
Published: February 2017

This paper presents an algorithm that estimates a measured output, which has been converted to a binary representation in order to transmit the information via a digital communication channel. The purpose of the estimator is to mitigate the effect of the delay due to transmitting the information across the communication channel. The algorithm uses each bit of the output sample to estimate the output sample value as it is being transmitted, and updates the control signal based on this estimate. Some basic analysis of this algorithm is presented along with simulations and a discussion on situations in which it could be beneficial.
Nonlinear Feedforward Control for Electrohydraulic Actuators With Asymmetric Piston Areas
Authors: Tripathi Abhinav , Sun Zongxuan
Published: February 2017

This paper presents a new design method of a nonlinear feedforward controller for electrohydraulic actuators with asymmetric piston areas. While the use of flatness based inversion of the plant model to design a feedforward controller has been reported for electrohydraulic actuators with symmetric piston area, the extension of this method to actuators with asymmetric piston areas is non-trivial. In asymmetric electrohydraulic actuators, the areas of the hydraulic piston are different in the two chambers, and hence, the amount of fluid going into one chamber of the actuator is not equal to the amount of fluid coming out of the other. This asymmetry leads to loss of flatness, and hence, flatness based inversion of the plant is no longer possible. In this paper, we present a method for calculation of the feedforward control signal for a given trajectory by numerically solving the inverse problem for the system. We demonstrate the effectiveness of the proposed feedforward controller by simulation of trajectory tracking in an asymmetric electrohydraulic actuator. For benchmarking, the tracking performance has been compared with three other feedforward schemes: a linearized model based Zero Phase Error Tracking (ZPET) feedforward controller, a nonlinear feedforward controller implementing an approximate plant inversion based on differential flatness, and a pressure feedback based feedforward controller.
Free Piston Engine Based Mobile Fluid Power Source
Authors: Liu Keyan , Zhang Chen , Sun Zongxuan
Published: February 2017

As a novel alternative of internal combustion engine (ICE), the free piston engine (FPE) eliminates the mechanical crankshaft and the associated constraints on its piston motion. Due to this extra degree of freedom and reduced inertia, the FPE is able to generate variable output power with higher efficiency and less emissions, while possessing a short response time. Hence, a hydraulic FPE (HFPE), which combines the FPE with a linear hydraulic pump, is a promising candidate as a fluid power source, especially for mobile applications. In this paper, such potential is investigated. The working principle of a prototype HFPE as a fluid power source is described and a comprehensive HFPE model is developed. Two novel control methods are proposed to regulate the output flow rate at any given load pressure so as to realize throttle-less fluid power control. Effectiveness of these two methods are demonstrated through simulation, where results clearly show the effectiveness of both methods in providing different output flow rates at given load pressure, thus demonstrating the HFPE’s capability as an efficient and flexible mobile fluid power source.
Failure Prognostics for In-Tank Fuel Pumps of the Returnless Fuel Systems
Authors: Taheri Ehsan , Gusikhin Oleg , Kolmanovsky Ilya
Published: February 2017

With the motivation to develop Condition Based Maintenance (CBM) strategies for the automotive vehicles, this paper considers a data-driven approach to the prognostics of the automotive fuel pumps. Focusing on the returnless type fuel delivery systems, our approach is based on estimating the fuel pump workload based on the model learned from the past driving history. Statistical reliability models are then exploited to estimate failure probability. These models are formulated in terms of the workload and updated from data available from vehicles in the field. Numerical examples which illustrate the proposed methodology are reported. Compared to alternative approaches, which are based on detailed physics-based degradation modeling and/or electrical signal analysis, our approach is data-driven, exploits connected vehicle analytics and reliability-based modeling, and has a potential to lead to simpler implementations.
Real-Time Powertrain Optimization Strategy for Connected Hybrid Electrical Vehicle
Authors: Mohd Zulkefli Mohd Azrin , Sun Zongxuan
Published: February 2017

Connected Vehicle (CV) technology, which allows traffic information sharing, and Hybrid Electrical Vehicles (HEV) can be combined to improve vehicle fuel efficiency. However, transient traffic information in CV environment necessitates a fast HEV powertrain optimization for real-time implementation. Model Predictive Control (MPC) with Linearization is proposed, but the computational effort is still prohibitive. The Equivalent Consumption Minimization Strategy (ECMS) and Adaptive-ECMS are proposed to minimize computation time, but unable to guarantee charge-sustaining-operation (CS). Fast analytical result from Pontryagin’s Minimum Principles (PMP) is possible but the input has to be unconstrained. Numerical solutions with Linear Programming (LP) are proposed, but over-simplifications of the cost and constraint functions limit the performance of such methods. In this paper, a nonlinear CS constraint is transformed into linear form with input variable change. With linear input and CS constraints, the problem is solved with Separable Programming by approximating the nonlinear cost with accurate linear piecewise functions which are convex. The piecewise-linear functions introduce new dimensionless variables which are solved as a large-dimension constrained linear problem with efficient LP solvers. Comparable fuel economy with Dynamic Programming (DP) is shown, with maximum fuel savings of 7% and 21.4% over PMP and Rule-Based (RB) optimizations. Simulations with different levels of vehicle speed prediction uncertainties to emulate CV settings are presented.
Battery State of Health Monitoring by Estimation of the Number of Cyclable Li-Ions
Authors: Zhou Xin , Stein Jeffrey L. , Ersal Tulga
Published: February 2017

This paper introduces a method to monitor battery state of health (SOH) by estimating the number of cyclable Li-ions, a health-relevant electrochemical variable. SOH monitoring is critical to battery management in particular for balancing the trade-off between maximizing system performance and minimizing battery degradation. However, SOH-related electrochemical variables cannot be directly measured non-invasively. Hence, estimation algorithms are needed to track those variables non-destructively while the battery is in use. In this paper, the extended Kalman filter (EKF) is used to estimate the number of cyclable Li-ions as an unknown battery parameter. Simulations are performed using an example parameter set for a hybrid-electric-vehicle battery whose cathode material is LiMn2O4 mixed with other Li-compounds to obtain estimation results under a typical electric vehicle current profile that consists of a 1 C constant current charge mode and a discharge current profile for an electric vehicle subject to the Urban Dynamometer Driving Schedule cycle. The simulations show promising results in estimation of the number of cyclable Li-ions using the EKF under the ideal conditions. Next, robustness of the algorithm under non-ideal conditions (i.e., with SOC estimation error, modeling error, and measurement noise) is analyzed, and it is shown that estimation of the number of cyclable Li-ions using the EKF preserves high accuracy even under these non-ideal conditions. The proposed estimation technique for the number of cyclable Li-ions can also be applied to other parameter sets and batteries with other cathode materials to monitor the SOH change resulting from any degradation mechanism that consumes cyclable Li-ions.
Output Feedback Stabilization of the Linearized Bilayer Saint-Venant Model
Authors: Diagne Ababacar , Tang Shuxia , Diagne Mamadou , Krstic Miroslav
Published: February 2017

We consider the problem of output feedback exponentially stabilizing the 1-D bilayer Saint-Venant model, which is a coupled system of two rightward and two leftward convecting transport partial differential equations (PDEs). The PDE backstepping control method is employed. Our designed output feedback controller is based on the observer built in this paper and the state feedback controller designed in [1], where the backstepping control design idea can also be referred to [2] and can be treated as a generalization of the result for the system with constant system coefficients [2] to the one with spatially-varying coefficients. Numerical simulations of the bilayer Saint-Venant problem are also provided to verify the result.
Preliminary Investigation of Provability of Li-Ion Macroscale Models Subject to Capacity Fade
Authors: Arunachalam Harikesh , Battiato Ilenia , Onori Simona
Published: February 2017

Estimating the remaining useful life of lithium-ion batteries is crucial for their application as energy storage devices in stationary and automotive applications. It is therefore important to understand battery degradation based on chemistry, usage patterns, and operating environment. Different degradation mechanisms that affect performance and durability of lithium-ion batteries have been identified over the past decades. Amongst them, the solid-electrolyte interface (SEI) layer growth has been observed to be the most influential cause of capacity fading. In this paper, we introduce for the very first time, a framework that evaluates the predictive ability of physics-based macroscopic models in capturing battery dynamics as function of their state-of-health (SoH). Using data from accelerated aging experiments, we identify the applicability conditions of classical electrochemical models. This analysis is performed using a phase diagram approach that involves parameters controlling the micro-scale dynamics inside the lithium-ion cell.
Improving Robotic Actuator Torque Density and Efficiency Through Enhanced Heat Transfer
Authors: Mazumdar Anirban , Spencer Steven J. , Hobart Clinton , Kuehl Michael , Brunson Gregory , Coleman Nadia , Buerger Stephen P.
Published: February 2017

Electric motors are a popular choice for mobile robots because they can provide high peak efficiencies, high speeds, and quiet operation. However, the continuous torque performance of these actuators is thermally limited due to joule heating, which can ultimately cause insulation breakdown. In this work we illustrate how motor housing design and active cooling can be used to significantly improve the ability of the motor to transfer heat to the environment. This can increase continuous torque density and reduce energy consumption. We present a novel housing design for brushless DC motors that provides improved heat transfer. This design achieves a 50% increase in heat transfer over a nominal design. Additionally, forced air or water cooling can be easily added to this configuration. Forced convection increases heat transfer over the nominal design by 79% with forced air and 107% with pumped water. Finally, we show how increased heat transfer reduces power consumption and we demonstrate that strategically spending energy on cooling can provide net energy savings of 4% – 6%.
H∞-Property of the Continuous-Time Extended Kalman Filter
Authors: Bonniwell Jennifer L. , Schneider Susan C. , Yaz Edwin E.
Published: February 2017

This work elucidates another theoretical property of the ubiquitous extended Kalman filter by analyzing the energy gain of the continuous-time extended Kalman filter used as a nonlinear observer in the presence of finite-energy disturbances. The analysis provides a bound on the ratio of estimation error energy to disturbance energy, which shows that the extended Kalman filter inherently has the H∞-property along with being the locally optimal minimum variance estimator. A special case of this result is also shown to be the H2-property of the extended Kalman filter.
Energy Harvesting and Damping Capability of Quarter-Car Test Bed
Authors: Algethami Abdullah A. , Kim Won-jong
Published: February 2017

Recovering and regenerating power in automotive applications has drawn significant interest recently. A car-suspension system can be modeled as a 2-DOF mass-spring-damper system. Active control used for the car suspension system produces results superior to other methods. In this study, a 3-phase linear generator is used to harvest energy and suppress vibration on a quarter-car suspension setup. The suspension system is analyzed to estimate the harvestable power and damping capability of the generator. Analysis for the generator and its efficiency are presented. Harvestable power of around 105 mW was achieved at a 3.5-Hz input disturbance. The regenerative suspension system can reduce the vibration of the sprung-mass acceleration by up to 22% in an indexed performance. Around 8.4 W used to drive the motor in active control was saved when the regenerative system was used. As a result, much energy can be saved by switching from the active to the energy-harvesting mode. A more efficient system can be designed by matching the mechanical and electromagnetic (EM) damping.
Consensus Control of Vibration in Smart Structures Based on Multimode Integral Resonance Method
Authors: Omidi Ehsan , Mahmoodi S. Nima
Published: February 2017

A new consensus based active vibration controller for distributed parameter system is developed and presented in this paper. The controller is made of multiple parallel first-order integrator filters that have consensus goal of suppressing resonant modes of an oscillating structure. Each actuator on the structure is designed to work as a node of the network. Together through the consensus communication topology of the controller the structural vibrations are suppressed. To validate the results a numerical study has been performed on a flexible cantilever beam structure. The results presented in this paper will show that the new controller works effectively, and is robust to failures and inconsistencies in the control system.
Optimization Based Weighting Matrices Design for Norm Optimal Iterative Learning Control
Authors: Ge Xinyi , Stein Jeffrey L. , Ersal Tulga
Published: February 2017

This paper focuses on Norm-Optimal Iterative Learning Control (NO-ILC) framework for Single-Input-Single-Output (SISO) Linear Time Invariant (LTI) systems and considers the weighting matrices design problem. The ideal design of weighting matrices should ensure Robust Monotonic Convergence (RMC) against modeling uncertainties while maximizing the convergence speed and minimizing the steady state error. The state-of-art RMC design methodologies either lead to conservative performance or require manual tunings. This paper provides a methodology to systematically achieve an optimal balance between robustness, convergence speed and steady state error. To this end, optimization problems are formulated at each frequency to maximize the convergence speed and minimize the steady state error. Two optimization formulations are proposed: one for an optimal nominal performance and one for an optimal performance against uncertainties. Both formulations offer a systematic approach for designing the weighting matrices for NO-ILC, thereby eliminating the manual tuning process and avoiding an unnecessarily conservative design. A simulation example is given to confirm the analysis and demonstrate the utility of the developed methodologies to design the weighting matrices.
A Task-Level Iterative Learning Control Algorithm for Accurate Tracking in Manipulators With Modeling Errors and Stringent Joint Position Limits
Authors: Bhounsule Pranav A. , Bapat Abhishek A. , Yamane Katsu
Published: February 2017

We present an iterative learning control algorithm for accurate task space tracking of kinematically redundant robots with stringent joint position limits and kinematic modeling errors. The iterative learning control update rule is in the task space and consists of adding a correction to the desired end-effector pose based on the tracking error. The new desired end-effector pose is then fed to an inverse kinematics solver that uses the redundancy of the robot to compute feasible joint positions. We discuss the stability, the rate of convergence and the sensitivity to learning gain for our algorithm using quasi-static motion examples. The efficacy of the algorithm is demonstrated on a simulated four link manipulator with joint position limits that learns the modeling error to draw the figure eight in 4 trials.
Robust H∞ Dynamic State-Feedback Control for Nonlinear Discrete-Time Systems via LMI-Based Regional Eigenvalue Assignment
Authors: Baker W. Alexander , Schneider Susan C. , Yaz Edwin E.
Published: February 2017

This paper uses Linear Matrix Inequality (LMI) techniques to apply regional eigenvalue assignment constraints to a dynamic state-feedback controller design for discrete-time systems with vanishing nonlinear perturbations. The controller design also incorporates the H∞ performance criterion. The regional eigenvalue assignment place the eigenvalues of the linear part of the system in two distinct regions, one region for the controller eigenvalues and one region for the observer eigenvalues, in such a way that the state estimation error goes to zero significantly faster than the state reaches steady state.
Implementation of State and Disturbance Estimation for Quadrotor Control Using Extended High-Gain Observers
Authors: Boss Connor J. , Lee Joonho , Aguiar Charles Carvalho de , Choi Jongeun
Published: February 2017

This paper proposes a discrete-time, multi-time-scale estimation and control design for quadrotors in the presence of external disturbances and model uncertainties. Assuming that not all state measurements are available, they will need to be estimated. The sample-data Extended High-Gain Observers are used to estimate unmeasured states, system uncertainties, and external disturbances. Discretized dynamic inversion utilizes those estimates and deals with an uncertain principal inertia matrix. In the plant dynamics, the proposed control forces the rotational dynamics to be faster than the translational dynamics. Numerical simulations and experimental results verify the proposed estimation and control algorithm. All sensing and computation is done on-board the vehicle.
High-Speed Broadband Real-Time Monitoring of Cell Viscoelasticity Reveals Oscillatory Myosin Activity
Authors: Yan Bo , Ren Juan , Zheng Xi , Liu Yue , Zou Qingze
Published: February 2017

This article presents the investigation of the dynamic behavior of the cytoskeleton of live human cells, enabled by a recently-developed control-based approach on scanning probe microscope (SPM). Mechanical behaviors of live cells play an important role in various cell physiological and pathological activities, and have been studied via various techniques and approaches. Studies of evolutions of mechanical properties of live cell, however, are still rather limited and scarce, due to the limitations of current instruments including SPM for single cellular measurements. Particularly, currently nanomechanical measurements using SPM is too slow to excite the mechanical behavior and then measure the corresponding response of life biological species over a large frequency range (broadband). Moreover, large uncertainty is induced in the in-liquid nanomechanical measurement using SPM, as in the indentation quantification, the effects of the acceleration force from the cantilever motion and the hydrodynamic force are not accounted for. The main contribution of this article is the use of a control-based nanomechanical protocol to interrogate the viscoelasticity oscillation of live human prostate cancer cell (PC-3 cells) and its dependence on myosin activities. The experiment results show that as the oscillation of static elastic modulus reported earlier in the literature, the oscillation of dynamic viscoelastic modulus measured is also periodic with a 200-second period. Moreover, as the elastic modulus oscillation, both the amplitude and the period of the viscoelasticity oscillation also strongly depend on the myosin activities, and closely regulated by the calcium density of the cytoskeleton.
Decentralized ℋ∞ Control in Microgrids to Mitigate Renewable Intermittency
Authors: Chu Cheong Matthew K. , Chen Dongmei , Du Pengwei
Published: February 2017

The goal of this paper is to control the dynamics of an islanded microgrid, a small-scale power system with distributed generation. An islanded microgrid is disconnected from the larger, main grid, and must maintain voltage and frequency standards using only local generation. As a result, islanded microgrids are more vulnerable to fluctuations in power supply and demand; this is especially relevant for intermittent renewable sources like wind turbines.

The system is stabilized with static-output-feedback ℋ∞ γ-suboptimal control. This is a multiple-input multiple-output (MIMO) controller in which the measured data is used as the direct input to a static gain matrix, whose output is in turn used to control the closed-loop system. In order to judge the performance of the decentralized controllers, the micgorid is controlled first in a centralized manner, where each controller has access to all measured state variables. Decentralized controllers are then synthesized by casting the problem as a convex program, where each controller only has access to locally measured variables. Control performance is compared with respect to a switched-on wind turbine, where we see that the decentralized controller effectively mitigates the system disturbance due to the renewable intermittency.
A Particle Filtering-Based Approach for Distributed Fault Diagnosis and Estimation of Multi-Robot Systems
Authors: Noursadeghi Elaheh , Raptis Ioannis
Published: February 2017

This paper deals with the problem of designing a distributed fault diagnosis and estimation algorithm for multi-robot systems that are subject to faults in the form of abrupt velocity biases. To solve this problem, the multi-robot collective is converted to a network of interconnected diagnostic nodes (DNs) that is deployed to monitor the health of the system. Each node consists of a reduced-order estimator with relative state measurements and an online parameter learning filter. The local estimator executes a distributed variation of the particle filtering algorithm using the local sensor measurements and the fault progression model of the robots. The parameter learning filter is used to obtain an approximation of the severity of faults. Numerical simulations demonstrate the efficiency of the proposed approach.
Downshifting Control Strategy for Dual Clutch Transmission With Single Clutch Slippage
Authors: Liu Jikai , Ma Biao , Li Heyan , Chen Man , Chen Jianwen
Published: February 2017

The cooperation mode between the engagement and disengagement clutches for vehicles equipped with Dual Clutch Transmission (DCT) is of vital importance to achieve a smooth gearshift, in particular for the downshift process as its unavoidable power interruption during the inertia phase. Hence, to elevate the performance of DCT downshifting process, an analytical model and experimental validation for the analysis, simulation and control strategy are presented. Optimized pressure profiles applied on two clutches are obtained based on the detailed analysis of downshifting process. Then, according to the analysis results, a novel control strategy that can achieve downshift task with only one clutch slippage is proposed. The system model is established on Matlab/Simulink platform and used to study the variation of output torque and speed in response to different charging pressure profiles and various external loads during downshifting process. Simulation results show that, compared with conventional control strategies, the proposed one can not only avoid the torque hole and power circulation, but shorten the shift time and reduce the friction work. Furthermore, to validate the effectiveness of the control strategy, the bench test equipped with DCT is conducted and the experiment results show a good agreement with the simulation results.
Energy Cost Optimization of HVAC Loads Under Time-Varying Electricity Price Signals
Authors: Bashash Saeid
Published: February 2017

This paper presents a dynamic programming approach to optimize energy cost of multiple interacting household appliances such as air conditioning systems and refrigerators with temperature flexibility, under time varying electricity price signals. We adopt a first order differential equation model with a binary (ON-OFF) switching control function for each load. An energy cost minimization problem is then formulated with a pair of constraints on the temperature lower and upper bounds, as well as an equality condition on the initial and final temperature states. We use dynamic programming to compute cost-optimal control inputs and temperature trajectories for a given electricity price profile and ambient temperature condition. To account for temperature deviation from its desired setpoint, a quadratic temperature deviation penalty is added to the cost function. Moreover, to minimize the control input chattering for equipment protection, the cost function is expanded to also minimize the number of on-off switching events. Results for the different weighting combinations of the optimization objectives provide useful insights on the optimal operation of individual and multiple interacting HVAC loads. In particular, we observe that the loads are desynchronized under the cost-optimal operation, in the presence of local (renewable) power generation. The presented optimization algorithm and observed results can lead to the development of novel model predictive and rule-based feedback control policies for optimal energy management in households.
Characterization of Resonant Mass Sensors Using Inkjet Deposition
Authors: Bajaj Nikhil , Rhoads Jeffrey F. , Chiu George T.-C.
Published: February 2017

Micro- and millimeter-scale resonant mass sensors have received widespread research attention due to their robust and highly-sensitive performance in a wide range of detection applications. A key performance metric associated with such systems is the sensitivity of the resonant frequency of a given device to changes in mass, which needs to be calibrated for different sensor designs. This calibration is complicated by the fact that the position of any added mass on a sensor can have an effect on the measured sensitivity, and thus a spatial sensitivity mapping is needed. To date, most approaches for experimental sensitivity characterization are based upon the controlled addition of small masses. These approaches include the direct attachment of microbeads via atomic force microscopy or the selective microelectrodeposition of material, both of which are time consuming and require specialized equipment. This work proposes a method of experimental spatial sensitivity measurement that uses an inkjet system and standard sensor readout methodology to map the spatially-dependent sensitivity of a resonant mass sensor — a significantly easier experimental approach. The methodology is described and demonstrated on a quartz resonator and used to inform practical sensor development.
Three-Stage Feedback Controller Design With Applications to a Three Time-Scale System
Authors: Radisavljevic-Gajic Verica , Milanovic Milos
Published: February 2017

A new technique was presented that facilitates design of independent full-state feedback controllers at the subsystem levels. Different types of local controllers, for example, eigenvalue assignment, robust, optimal (in some sense L1, H2, H∞, ...) may be used to control different subsystems. This feature has not been available for any known linear feedback controller design. In the second part of the paper, we specialize the results obtained to the three time-scale linear systems (singularly perturbed control systems) that have natural decomposition into slow, fast, and very fast subsystems. The proposed technique eliminates numerical ill-condition of the original three-time scale problems.
Experimental Stimulation of EDL Mouse Muscle With a Small Scale Two-Coil System
Authors: Jaramillo Cienfuegos Paola , Burks Garret , Leonessa Alexander , Abaid Nicole
Published: February 2017

As a muscle activation treatment, magnetic stimulation can elicit current flow through appropriate amplitude and frequency to generate electrical currents, which will prompt activation in the muscle tissue. The design of an electromagnetic system serves as an alternative to direct electrical stimulation for treating muscles located deep inside the tissue, such as the laryngeal muscles, stimulated via output-based control systems. Through magnetic induction, we can implement electrical stimulation and target specific muscle activation. In light of this approach, our goal is to incorporate feedback control using an electromagnetic stimulation system. These studies, therefore, focus on assessing a linear Proportional-Integral (PI) controller and two nonlinear controllers, Model Reference Adaptive Controller (MRAC) and an Adaptive Augmented PI (ADP-PI) system, to identify the most appropriate controller providing effective stimulation of the muscle. Our work focuses on the feasibility of our system to carry out in vitro experiments on mouse skeletal muscle and the characterization of the two-coil system for future design of implantable systems in humans.