bluuebunny/crossref_metadata_2025 huggingface dataset:
Limit Cycle Analysis of Flexible Structures Under Discontinuous Feedback Control
Authors: Borre Michael , Flashner Henryk
Published: February 2011

A method for calculating all periodic solutions and their domains of attraction for flexible systems under nonlinear feedback control is presented. The systems considered consist of mechanical systems with many flexible modes and a relay type controller coupled with a PID control law operating in a feedback configuration. The proposed approach includes three steps. First, limit cycle frequencies and periodic fixed points are computed exactly, using a block diagonal state-space modal representation of the plant dynamics. Then the relay switching surface is chosen as the Poincare mapping surface and is discretized using the cell mapping method. Finally, the region of attraction for each limit cycle is computed using the cell mapping algorithm and employing an error based convergence criterion. An example consisting of a system with two modes, a relay with hysteresis and a PD controller is used to demonstrate the proposed approach.
Acquisition of Fear and Extinction in Lateral Amygdala: A Modeling Study
Authors: Pendyam Sandeep , Kim Dongbeom , Quirk Gregory J. , Nair Satish S.
Published: February 2011

The lateral nucleus of amygdala (LA) is known to be a critical storage site for conditioned fear memory. Synaptic plasticity at auditory inputs to the dorsal LA (LAd) is critical for the formation and storage of auditory fear memories. Recent evidence suggests that two different cell populations (transient- and long-term plastic cells) are present in LAd and are responsible for fear learning. However, the mechanisms involved in the formation and storage of fear are not well understood. As an extension of previous work, a biologically realistic computational model of the LAd circuitry is developed to investigate these mechanisms. The network model consists of 52 LA pyramidal neurons and 13 interneurons. Auditory and somatosensory information reaches LA from both thalamic and cortical inputs. The model replicated the tone responses observed in the two LAd cell populations during conditioning and extinction. The model provides insights into the role of thalamic and cortical inputs in fear memory formation and storage.
Optimal Full Information H2 Guaranteed Cost Control of Discrete-Time Systems
Authors: Conway Richard , Horowitz Roberto
Published: February 2011

This paper presents, for discrete-time LTI systems with unstructured dynamic uncertainty, a methodology for designing full information controllers which minimize the upper bound on robust H2 performance given in [1]. It is first shown that this optimal control problem can be cast as a semi-definite program. Then, it is shown that this optimization problem can be solved efficiently and accurately using discrete algebraic Riccati equations.
System Identification of Small Loudspeakers Using ARMA Model
Authors: Choi Jaewon , Nakhaeinejad Mohsen , Bryant Michael D.
Published: February 2011

This study illustrates a data driven system identification method for loudspeaker model estimation using the knowledge of the underlying physics of loudspeakers. In this study, diaphragm displacement is analyzed to estimate the model structure and parameters based on impulse response equivalent sampling and autoregressive moving average model. The estimated loudspeaker models are compared in the frequency response function plot. It is shown that the autoregressive moving average (ARMA) based loudspeaker models are comparable to the model estimated by the conventional method based on electrical impedance. Also ARMA modeling strategies with and without knowledge of the physics-based model are compared. Some issues related to ARMA modeling are addressed.
Intersample Discretization of Control Inputs for Flexible Systems With Quantized Cellular Actuation
Authors: Schultz Joshua A. , Ueda Jun
Published: February 2011

Piezoelectrically driven cellular actuators are a technology inspired by biological muscles. Like muscle tissue, several serial and parallel combinations act in concert to achieve the desired motion. In order to simplify the drive electronics and mitigate the effect of hysteresis in piezoelectric materials, it is desired to restrict each input to simple on-off commands. This quantizes the actuation greatly. The cellular actuators also have a number of lightly damped flexible modes, which may be higher than the Nyquist frequency of the discrete–time controller. These may still cause long settling times. We propose a method to convert a continuously variable control input from a controller whose design does not consider quantization and flexible effects to a quantized signal that can be implemented by the actuator which also reduces oscillation in known lightly damped modes.
Self-Tuning Fuzzy Sliding Controller for the Ship Heading Problem
Authors: Khaled Nassim , Chalhoub Nabil G.
Published: February 2011

A self-tuning fuzzy-sliding mode controller is presented in the current work. It aims at combining the advantages of the variable structure systems (VSS) theory with the self-tuning fuzzy logic controller. Neither the development of an accurate dynamic model of the plant nor the construction of a rule-based expert system is required for designing the controller. The only requirement is that the upper bound of the modeling uncertainties has to be known. The stability of the controlled system is ensured by forcing the tuning parameter to satisfy the sliding condition. The controller is implemented to control the heading of an under-actuated ship. The simulation results demonstrate the robust performance of the controller in accurately tracking the desired yaw angle specified by the guidance system in the presence of considerable modeling imprecision and environmental disturbances.
Stochastic Estimation of the Multi-Variable Mechanical Impedance of the Human Ankle With Active Muscles
Authors: Rastgaar Mohammad A. , Ho Patrick , Lee Hyunglae , Krebs Hermano Igo , Hogan Neville
Published: February 2011

This article compares stochastic estimates of multi-variable human ankle mechanical impedance when ankle muscles were fully relaxed, actively generating ankle torque or co-contracting antagonistically. We employed Anklebot, a rehabilitation robot for the ankle, to provide torque perturbations. Muscle activation levels were monitored electromyographically and these EMG signals were displayed to subjects who attempted to maintain them constant. Time histories of ankle torques and angles in the Dorsi-Plantar flexion (DP) and Inversion-Eversion (IE) directions were recorded. Linear time-invariant transfer functions between the measured torques and angles were estimated for the Anklebot alone and when it was worn by a human subject, the difference between these functions providing an estimate of ankle mechanical impedance. High coherence was observed over a frequency range up to 30 Hz. The main effect of muscle activation was to increase the magnitude of ankle mechanical impedance in both DP and IE directions.
Development of an Adaptive System ID Method for Enabling Advanced E-Beam Sweep Pattern Design
Authors: Speyerer Emerson , Gevelber Michael , Radgowski Dennis
Published: February 2011

Electron beam (E-beam) vacuum deposition is extensively used for the production of precision optical coatings due to its ability to economically deposit a wide range of source materials. To manufacture superior optical devices, high precision optical coatings are required. One measure of the process capabilities is the accuracy and repeatability of each layer’s optical thickness. A major limitation to controlling optical thickness, especially for large-scale and multi-layer optics, is the variability in the vapor plume geometry due to non-uniform evaporation of the source material. For sublimating materials, like silica, variations in the size and direction of the vapor plume has been attributed to topography on the melt surface, which forms due to uneven source depletion caused by non-uniform heating. In this paper, an experimentally based adaptive system identification method is used to develop custom sweep patterns to control a complicated nonlinear system with both process and equipment nonlinearities.
Dynamic Performance of Nonlinear 100X Displacement Amplification Piezoelectric Actuator
Authors: Neal Devin , Asada H. Harry
Published: February 2011

The dynamic frequency response of a nonlinear piezoelectric amplification mechanism capable of over 150 fold displacement amplification is presented. Research to amplify the displacement of piezoelectric actuators has included flexure based approaches that utilize geometric configuration, and has included frequency based approaches that utilize resonance and small steps to contribute to a full motion. The dynamic operation of the actuator presented here utilizes the benefits from both of these methods. The geometry allows for great displacement amplification, and operation within a specific frequency band allows for the exploitation of a nonlinear singularity. The actuator has three distinct modes of dynamic operation, one of which achieves significant displacement by utilizing momentum to pass through a singular configuration. A nonlinear model, linear models for each frequency response mode, and multiple prototypes are presented. This actuator operating in the high displacement frequency band is promising as an input actuator for stepping mechanisms.
Estimating Traction Coefficients of Friction for Small-Scale Robotic Tracked Vehicles
Authors: Dar Tehmoor M. , Longoria Raul G.
Published: February 2011

A method is presented for using an extended Kalman filter with state noise compensation to estimate the trajectory, orientation, and coefficients of friction for a small-scale robotic tracked vehicle. The ultimate goal of the method is to enable terrain property estimation particularly during laboratory and field-testing utilizing onboard sensor data and/or other sources. A methodology is described that relies on kinematic and dynamic models for skid-steering, as well as tractive force models parameterized by key soil parameters. Favorable results for estimating coefficients of friction are presented based on experimental data collected for laboratory and field testing with an iRobot® PackBot™. Preliminary results confirm the dependence of coefficients of friction on vehicle trajectory turning radius and velocity.
Mathematical Modelling of Near-Hover Insect Flight Dynamics
Authors: Cheng B. , Deng X.
Published: February 2011

Using a dynamically scaled robotic wing, we studied the aerodynamic torque generation of flapping wings during roll, pitch, and yaw rotations of the stroke plane. The total torque generated by a wing pair with symmetrical motions was previously known as flapping counter-torques (FCTs). For all three types of rotation, stroke-averaged FCTs act opposite to the directions of rotation and are collinear with the rotational axes. Experimental results indicate that the magnitude of FCTs is linearly dependent on both the flapping frequency and the angular velocity. We also compared the results with predictions by a mathematical model based on quasi-steady analyses, where we show that FCTs can be described through consideration of the asymmetries of wing velocity and the effective angle of attack caused by each type of rotation. For roll and yaw rotations, our model provided close estimations of the measured values. However, for pitch rotation the model tends to underestimate the magnitude of FCT, which might result from the effect of the neglected aerodynamics, especially the wake capture. Similar to the FCT, which is induced by body rotation, we further provide a mathematical model for the counter force induced by body translation, which is termed as flapping counter-force (FCF). Based on the FCT and FCF models, we are able to provide analytical estimations of stability derivatives and to study the flight dynamics at hovering. Using fruit fly (Drosophila) morphological data, we calculated the system matrix of the linearized flight dynamics. Similar to previous studies, the longitudinal dynamics consist of two stable subsidence modes with fast and slow time constants, as well as an unstable oscillatory mode. The longitudinal instability is mainly caused by the FCF induced by an initial forward/backward velocity, which imparts a pitch torque to the same direction of initial pitch velocity. Similarly, the lateral dynamics also consist of two stable subsidence modes and an unstable oscillatory mode. The lateral instability is mainly caused by the FCF induced by an initial lateral velocity, which imparts a roll torque to the same direction of initial roll velocity. In summary, our models provide the first analytical approximation of the six-degree-of-freedom flight dynamics, which is important in both studying the control strategies of the flying insects and designing the controller of the future flapping-wing micro air vehicles (MAVs).
Simultaneous Unknown State and Input Estimation With Application to Virtual Air Charge and EGR Sensors for Automotive Engines
Authors: Liu Chia-Shang
Published: February 2011

This paper addresses the problem of simultaneous estimation of unknown state and input for a class of nonlinear systems. Under certain minimum-phase conditions, the unknown states and inputs can be recovered asymptotically with high gain observers. The design of the observer uses the perfect observation scheme such that a restrictive input-output rank condition can be relaxed. It can be shown that the proposed estimation approach of the unknown input is in the form of the integration of estimation error signals. Thanks to the integrator the common issue of measurement noise corruption of the recovered unknown inputs can be significantly reduced. The proposed approach is applied to real-time estimate in-cylinder air charge and exhaust gas recirculation (EGR) flow rate of automotive internal combustion engines which are important factors for tailpipe emission reduction.
A Method to Find Non-Zero Operating Point Volterra Models for Port-Based Ordinary Differential Equations
Authors: Motato Eliot , Radcliffe Clark , Viveros Jose Luis
Published: February 2011

Nonlinear physical systems frequently perform around constant non-zero input-output operating conditions. This local behavior can be modeled using port-based nonlinear ordinary differential equations (ODEs). An ODE local solution around an specific input-output operating point can be obtained through the Volterra transfer function (VTF) model. In a past work a procedure for obtaining MIMO Volterra models from port-based nonlinear ODEs was presented. This previous work considered only systems operating at zero input-output conditions subject to linear inputs. In this work the process for obtaining MIMO Volterra transfer functions is extended for systems operating at non-zero input-output conditions. This extension also allows systems that are nonlinear functions of their inputs and input derivatives.
Design Properties That Affect Controller Gain and Available Bandwidth of Non-Minimum Phase Membrane Humidifiers
Authors: Hall John F. , Mecklenborg Christine A. , Chen Dongmei
Published: February 2011

The water vapor transfer across a membrane exhibits non-minimum phase behavior. This paper shows that the competing dynamics of heat and mass transfer cause the membrane humidifier to have a non-minimum phase zero. Even though the non-minimum phase zero exists in the disturbance-output loop, it will limit the feedback controller gain because the disturbance-output loop is coupled with the input-output loop. The membrane properties and heat transfer parameters affect the non-minimum phase zero location. The impact on available feedback control gain and system bandwidth is analyzed in relation to changes of the non-minimum phase zero during hardware design.
Dynamic Analysis and Control of a Portable Cherrypicker
Authors: Maleki Ehsan , Pridgen Brice , Xiong Jing Qi , Singhose William
Published: February 2011

Cherrypickers are an important class of machines that can lift people to great heights. Understanding the dynamics and stability of these machines is crucial for efficient and safe operation. A dynamic model has been developed to capture the oscillatory dynamics of the machine as a function of the configuration and mass properties. Simulation studies reveal the complex dynamic behavior of the machine. In many cases, the oscillation of the endpoint bucket causes difficulties and dangers for the operators. An input-shaping controller has been added to the system to decrease the oscillatory dynamics. A portable cherrypicker is being developed for use in both education and research. The cherrypicker will be used as an experimental testbed in an advanced controls course at the Massachusetts Institute of Technology. The MIT students will use the machine to verify their theoretical models of the dynamic behavior, as well as evaluate control systems they develop to improve performance. Concurrently, students at the Georgia Institute of Technology will use the machine in teleoperation mode to conduct similar experiments. The MIT and Georgia Tech students will work together to conduct meaningful research on the cherrypicker testbed for their course projects. This paper describes the developments and results of the project to date.
Bifurcation and Control of Cardiac Alternans
Authors: Xia Henian , Zhao Xiaopeng
Published: February 2011

Cardiac alternans is a marker of sudden cardiac arrest, the leading cause of death in the United States that kills hundreds of thousands of Americans each year. In the language of nonlinear dynamics, the onset of cardiac alternans is induced by a period-doubling bifurcation. In this work, we explore the bifurcation and control of cardiac alternans in a fiber based on numerical analyses of the seminal amplitude equation derived by Echebarria and Karma. First, we seek the solution of the amplitude equation using a series expansion. Then, detailed numerical bifurcation analyses are carried out to illustrate the spatiotemporal patterns of cardiac alternans. We demonstrate that secondary bifurcations lead to multiple unstable patterns, which impose difficulties in feedback control of alternans. Effects and limitations of feedback control algorithms are explored. The theoretical analyses here help to improve the understanding of the mechanisms of alternans in cardiac tissue.
Synthesis and Analysis of Control Laws for Swarm of Mobile Robots Emulating Ant Foraging Behavior
Authors: Ramakrishnan Subramanian , Kumar Manish
Published: February 2011

Ant foraging behavior has inspired research in a number of areas including distributed problem solving such as optimization and task allocation and mobile robot navigation. In the area of swarm robotic systems, ant foraging behavior has been largely modeled via behavior based techniques and analyzed using cellular automata. Development of continuous time models for ant foraging can potentially provide insights into new mechanisms and behaviors used by ants that provide self-organizing capabilities to the ant colony. This paper presents a distributed control law in continuous time that combines gradient following for pheromone concentration as well as food scent with random motion seen in ants. The paper also provides a continuous time model for pheromone laying in a 2D environment and carries out a preliminary numerical stability analysis of the solutions. Extensive simulation studies confirm emergent behaviors seen in ant systems such as trail formation and convergence to single food site. In addition, the paper examines the effect of randomness on robustness of convergence to a single food site.
Reduced-Order Cue-Signal-Response Modeling for Angiogenic Cell Migration Control: A Principal Signal Approach
Authors: Asada H. Harry
Published: February 2011

A cell’s behavior in response to stimuli is governed by a signaling network, called cue-signal-response. Endothelial Cells (ECs), for example, migrate towards the source of chemo-attractants by detecting cues (chemo-attractants and their concentration gradient), feeding them into an intra-cellular signaling network (coded internal state), and producing a response (migration). It is known that the cue-signal-response process is a nonlinear, dynamical system with high dimensionality and stochasticity. This paper presents a system dynamics approach to modeling the cue-signal-response process for the purpose of manipulating and guiding the cell behavior through feedback control. A Hammerstein type model is constructed by representing the entire process in two stages. One is the cue-to-signal process represented as a nonlinear feedforward map, and the other is the signal-to-response process as a stochastic linear dynamical system, which contains feedback loops and auto-regressive dynamics. Analysis of the signaling space based on Singular-Value Decomposition yields a set of reduced order synthetic signals, which are used as inputs to the dynamical system. A prediction-error method is used for identifying the model from experimental data, and an optimal system order is determined based on Akaike’s Information Criterion. The resultant low order model is capable of predicting the expected response to cues, and is directly usable for feedback control. The method is applied to an in vitro angiogenic process using microfluidic devices.
Dynamic Thermal Model of PEM Fuel Cells for MIMO Control Design
Authors: Hadisujoto Budi , Refai Rehan , Chen Dongmei , Moon Tess J.
Published: February 2011

This paper discusses the development of a PEM fuel cell stack model that takes into account dynamic thermal and humidity effects. The outputs of the model are in good agreement with experimental results in literature. This nonlinear MIMO system is linearized and then analyzed by using the Relative Gain Array. The objectives are to understand the coupling between the control loops, and to pair the inputs to the outputs to achieve decentralized SISO control. The control inputs for the RGA are the compressor voltage and coolant flow rate. The performance indices are the net power output and fuel cell temperature. Analysis suggests that in most cases the stack temperature is strongly affected by the coolant flow rate, and the net power output is influenced by the compressor voltage. The coupling of the two loops is caused by the coupling of the heat and mass transfer dynamics during the fuel cell operation. When the fuel cell operates at high temperature and high current demand, the coupling of the two loops attenuates. Therefore, the decentralized SISO control is applicable when the temperature and current are high.
Linear Stability Control of Offshore Wind Turbines
Authors: Mecklenborg Christine A. , Rouenhoff Philipp , Chen Dongmei
Published: February 2011

Offshore wind farms in deep water are becoming an attractive prospect for harnessing renewable energy and reducing dependence on fossil fuels. One area of major concern with offshore wind turbines is stability control. The same strong winds that give deep water turbines great potential for energy capture also pose a threat to stability, along with potentially strong wave forces. We examine development of state space controllers for active stabilization of a spar-buoy floating turbine. We investigate linear state feedback with a state observer and evaluate response time and disturbance rejection of decoupled SISO controllers.
Control of Wind Turbine Systems With Input Saturation Using Online Trajectory Replanning
Authors: Lu Lu , Yao Bin
Published: February 2011

For wind turbine control systems, if the wind speed changes rapidly, traditional maximum power point tracking strategy will have problems caused by input saturation due to the fast changing desired rotor speed and the large inertia of rotor. This paper proposes a new control strategy to effectively deal with the input saturation problem of wind turbine systems. A double-loop control structure is developed. In the inner loop, a feedback controller is designed to regulate the rotor speed with guaranteed tracking accuracy in spite of various types of uncertainties. In the outer loop, an online trajectory replanning algorithm is implemented to regenerate the desired rotor speed and pitch angle to make the closed-loop system satisfy the input and speed constraints while making the converging speed of the replanned trajectory to the optimal desired trajectory as fast as possible so that the energy loss during transient period is minimized. Simulation result using FAST demonstrates the effectiveness of the proposed strategy.
Maglev-Girder Interaction for Centralized and De-Centralized Controllers
Authors: Alberts Thomas , Aly Mohamed , Omran Ashraf
Published: February 2011

This paper presents a comparison between the centralized and de-centralized controllers of a magnetically levitated vehicle. The simulation accounts for the interaction between the vehicle and girder through the control electromagnetic levitation force of the vehicle. In this way, the effects of: controller dynamics, electrodynamics, vehicle dynamics, and vehicle velocity are considered in order to provide a more realistic simulation. The main purpose of this work is to qualify the performance of each controller in sustaining an acceptable ride quality referred to ISO2631.
Predictive Control of Autonomous Ground Vehicles With Obstacle Avoidance on Slippery Roads
Authors: Gao Yiqi , Lin Theresa , Borrelli Francesco , Tseng Eric , Hrovat Davor
Published: February 2011

Two frameworks based on Model Predictive Control (MPC) for obstacle avoidance with autonomous vehicles are presented. A given trajectory represents the driver intent. An MPC has to safely avoid obstacles on the road while trying to track the desired trajectory by controlling front steering angle and differential braking. We present two different approaches to this problem. The first approach solves a single nonlinear MPC problem. The second approach uses a hierarchical scheme. At the high-level, a trajectory is computed on-line, in a receding horizon fashion, based on a simplified point-mass vehicle model in order to avoid an obstacle. At the low-level an MPC controller computes the vehicle inputs in order to best follow the high level trajectory based on a nonlinear vehicle model. This article presents the design and comparison of both approaches, the method for implementing them, and successful experimental results on icy roads.
Controllability and Observability of a Large Scale Thermodynamical System via Connectability Approach
Authors: Permana Virdiansyah , Shoureshi Rahmat
Published: February 2011

This study presents a new approach to determine the controllability and observability of a large scale nonlinear dynamic thermal system using graph-theory. The novelty of this method is in adapting graph theory for nonlinear class and establishing a graphic condition that describes the necessary and sufficient terms for a nonlinear class system to be controllable and observable, which equivalents to the analytical method of Lie algebra rank condition. The directed graph (digraph) is utilized to model the system, and the rule of its adaptation in nonlinear class is defined. Subsequently, necessary and sufficient terms to achieve controllability and observability condition are investigated through the structural property of a digraph called connectability. It will be shown that the connectability condition between input and states, as well as output and states of a nonlinear system are equivalent to Lie-algebra rank condition (LARC). This approach has been proven to be easier from a computational point of view and is thus found to be useful when dealing with a large system.
Computation of the Instantaneous Frictional Losses of Internal Combustion Engine Components
Authors: Kfoury Giscard A. , Chalhoub Nabil G.
Published: February 2011

An inverse dynamics scheme, based on a detailed differential-algebraic model of the crank-slider mechanism of a single cylinder internal combustion (IC) engine, is developed for the computation of the instantaneous frictional losses of engine components. The proposed approach requires accurate measurements of the independent and superfluous coordinates of the crank-slider mechanism as well as their time derivatives. This was achieved by implementing a sliding mode observer, previously developed by the authors, to provide the required estimates of the state variables. The aforementioned observer is suitable for use with differential-algebraic nonlinear equations of motion and was shown to be robust to both modeling imprecision and external disturbances. The digital simulation results show the capability of the combined inverse dynamics scheme with the observer in producing good estimates of the instantaneous frictional losses of the various engine components.
Modeling of a Two-Stroke Free-Piston Engine With HCCI Combustion
Authors: Li Ke , Santiago Wilson , Sun Zongxuan
Published: February 2011

This paper describes the modeling of a two-stroke dual chamber free piston engine (FPE) running homogeneous charge compression ignition (HCCI) combustion with an embedded linear alternator and a hydraulic pump. Variable compression ratio of FPE enables multi-fuel operation. Furthermore, the addition of an electric generator and hydraulic pump ensure the engine to have both high energy density and power density. These three concepts combined, will make for a highly efficient and flexible approach for engine operation. However, the characteristic of FPE also brings challenges in engine control. We propose a control oriented model that provides detailed gas exchange processes between intake/exhaust and cylinder volume, and the dynamic interactions between combustion, the linear alternator and the hydraulic pump. Influences of fuel and valve timing on engine performance are studied. Simulated engine dynamics are observed to have significant differences from conventional internal combustion engines.
A Real-Time Data Compression and Occupancy Grid Map Generation for Ground-Based 3D LIDAR Data Using Wavelets
Authors: Im Jeong Joon , Leonessa Alexander , Kurdila Andrew
Published: February 2011

A map generated from ground-based 3D LIDAR data is a critical component for autonomous vehicle navigation using a vision based sensor. When the size of a map is large and the number of grid cells is relatively big, managing the map associated with a dense data set from 3D LIDAR scanner is a demanding task. Wavelets serve as the basis for an efficient compression scheme which makes it possible to significantly reduce processing effort to generate and manage a grid map in real-time. This paper proposes a novel approach to generate an occupancy map from compressed measurement signals. A one-dimensional Haar wavelet transform has been applied to compress 3D LIDAR data, from which occupancy maps have been generated. Our experimental results show that this method performs well to provide an autonomous vehicle with rich 3D environment information.
A Fully Automated System for the Preparation of Samples for Cryo-Electron Microscopy
Authors: Thompson Zachary J. , Johnson Kevin L. , Overby Nicolas , Chidi Jessica I. , Pryor William K. , O’Malley Marcia K.
Published: February 2011

The preparation of specimens for cryo-electron microscopy is currently a labor and time intensive process, and the quality of resulting samples is highly dependent on both environmental and procedural factors. Specimens must be applied to sample grids in a high-humidity environment, frozen in liquid ethane, and stored in liquid nitrogen. The combination of cryogenic temperatures and humidity-control mandates the segregation of the humidity-controlled environment from the cryogenic environment. Several devices which automate portions of the specimen preparation process are currently in use; however, these systems still require significant human interaction in order to create viable samples. This paper describes a fully automated system for specimen preparation. The resulting system removes the need for human input during specimen preparation, improves process control, and provides similar levels of environmental control. Early testing shows that the resulting system is capable of manipulating samples in an autonomous manner while providing performance similar to existing systems.
Interpretation of the Directional Properties of Voluntarily Modulated Human Ankle Mechanical Impedance
Authors: Ho Patrick , Lee Hyunglae , Rastgaar Mohammad A. , Krebs Hermano Igo , Hogan Neville
Published: February 2011

This article presents the results of two in-vivo studies providing measurements of human static ankle mechanical impedance. Accurate measurements of ankle impedance when muscles were voluntarily activated were obtained using a therapeutic robot, Anklebot, and an electromyographic recording system. Important features of ankle impedance, and their variation with muscle activity, are discussed, including magnitude, symmetry and directions of minimum and maximum impedance. Voluntary muscle activation has a significant impact on ankle impedance, increasing it by up to a factor of three in our experiments. Furthermore, significant asymmetries and deviations from a linear two-spring model are present in many subjects, indicating that ankle impedance has a complex and individually idiosyncratic structure. We propose the use of Fourier series as a general representation, providing both insight and a precise quantitative characterization of human static ankle impedance.
Motion Planning Under External Constraints for Redundant Dynamic Systems
Authors: Kim Joo H. , Abdel-Malek Karim , Xiang Yujiang , Yang Jingzhou James , Arora Jasbir S.
Published: February 2011

Dynamics of mechanical systems during motion usually involves reaction forces and moments due to the interaction with external objects or constraints from the environment. The problem of predicting the external reaction loads under rigid-body assumption has not been addressed extensively in the literature in terms of optimal motion planning and simulation. We propose a formulation of determining the external reaction loads for redundant systems motion planning. For dynamic equilibrium, the resultant reaction loads that include the effects of inertia, gravity, and general applied loads, are distributed to each contact point. Unknown reactions are determined along with the system configuration at each time step using iterative nonlinear optimization algorithm. The required actuator torques as well as the motion trajectories are obtained while satisfying given constraints. The formulation is applied to several example motions of multi-rigid-body systems such as a simple welding manipulator and a highly articulated whole-body human mechanism. The example results are compared with the cases where the reactions are pre-assigned.
Accuracy and Optimal Timing of Activity Measurements in Estimating Absorbed Dose of Radioiodine in the Treatment of Graves’ Disease
Authors: Merrill S. , Chipkin S. R. , Horowitz J. , Hollot C. V. , Traino A. C. , Chait Y.
Published: February 2011

Calculation of the therapeutic activity of radioiodine 131I for individualized dosimetry in the treatment of Graves’ disease requires an accurate estimate of the thyroid absorbed radiation dose based on a tracer activity administration of 131I. Common approaches (Marinelli-Quimby formula, MIRD algorithm) use, respectively, the effective half-life of radioiodine in the thyroid and the cumulative activity. Many physicians perform one, two, or at most three tracer dose activity measurements at various times and calculate the required therapeutic activity by ad hoc methods. In this paper, we study the accuracy of estimates of four “target variables”: cumulated activity, effective half-life, maximum activity, and time of maximum activity in the gland. Clinical data from 41 patients who underwent 131I therapy for Graves’ disease at the University Hospital in Pisa, Italy, are used for analysis. The radioiodine kinetics are described using a nonlinear mixed-effects model that includes a measurement error term, and the distributions of the target variables in the patient population are characterized. Using minimum root mean squared error (RMSE) as the criterion, optimal 1-, 2-, and 3-point sampling schedules are determined for estimation of the target variables, and probabilistic bounds are given for the errors under the optimal designs. An optimization algorithm is developed for computing target variables for arbitrary 1-, 2-, and 3-point activity measurements. Taking into consideration 131I effective half-life in the thyroid and measurement noise, the optimal 1-point design for cumulated activity is a measurement one week following the tracer dose. Additional measurements give only a slight improvement in accuracy.
Rollover Prevention of Multi-Body Ground Vehicles Extending LQR Design for Control Coupled Output Regulation
Authors: Yedavalli Rama K. , Huang Hsun-Hsuan
Published: February 2011

In this paper, a novel control system analysis and design technique is presented by transforming rollover index minimization as an optimal control problem in the popular Linear Quadratic Regulator (LQR) control design framework. This results in a ‘control coupled output regulation’ problem because of the coupled terms in state and control variables in the performance index. There are no guidelines available for the selection of state and control weightings for the coupled case. In this paper, we present considerable insight into the major differences in the optimal control problem formulation for the uncoupled and coupled cases and provide guidelines for weight selections by taking into consideration the interaction (or coupling) between state and control terms and using the property of ‘Output Zeroing’ controller. The proposed analysis and design method is illustrated with rollover prevention control for a multi-body Ground Vehicle using the active steering control and active roll control respectively.
Nonlinear Model-Based Adaptive Control of a Solenoid-Valve System
Authors: Lee DongBin , Nataraj C. , Naseradinmousavi Peiman
Published: February 2011

In this paper, a model-based control algorithm is developed for a solenoid-valve system. Solenoids and butterfly valves have uncertainties in multiple parameters in the model, which make the system difficult to adjust to the environment. These are further complicated by combining the solenoid and butterfly dynamic models. The control objective of a solenoid-valve system is to position the angle of the butterfly valve through the electric-driven actuator in spite of the complexity presented by uncertainties. The novelty of the controller design is that the current source of the solenoid valve from the model of the electromagnetic force is substituted for the control input in order to reach the set-point of the butterfly disk based on the error signals, overcoming the uncertainties represented by lumped parameters groups, and a stable controller is designed via the Lyapunov-based approach for the stability of the system and obtaining the control objective. The parameter groups are updated by adaptation laws using a projection algorithm. Numerical simulation is shown to demonstrate good performance of the proposed approach.
Characterizing Driving Skill Based on Entropy Analysis of Steering Frequency Response
Authors: Tan Han-Shue , Bu Fanping , Huang Jihua , Chin Yuen-Kwok
Published: February 2011

As a first step towards a dynamic control-oriented driver model that can describe various levels of driving skill in the driver’s primary vehicle control functions, this paper attempts to recognize the driving skill manifested in the low-level control characteristics. Vehicle tests on a DLC course were conducted with twenty subjects of different skill levels. A variance-based analysis was applied to the steering angle to generate both the frequency responses and the time sequences for frequency-domain and time-domain analysis. Two entropy measures are developed to evaluate the effectiveness of drivers’ steering control, and preview errors are used to provide an absolute measure for drivers’ preview performance. Simple rules using these three measures are developed, and data analysis verifies that the above three measures can effectively distinguish the driving skill levels of the twenty subjects participated in the DLC vehicle test.
Optimal H∞ Control for Linear Periodically Time-Varying Systems in Hard Disk Drives
Authors: Nie Jianbin , Conway Richard , Horowitz Roberto
Published: February 2011

This paper discusses optimal H∞ control synthesis via discrete Riccati equations for discrete linear periodically time-varying (LPTV) systems. Based on the results presented in [1], an explicit minimum entropy H∞ controller for general time-varying systems is obtained. The control synthesis technique is subsequently applied to LPTV systems and it is shown that the resulting controllers are also periodically time varying. In order to demonstrate the effectiveness of the proposed control synthesis technique, both single-rate and multi-rate discrete-time minimum entropy H∞ track-following control designs for hard disk drives are considered. It is shown, via a comprehensive simulation study, that track-following controllers designed using the H∞ synthesis technique proposed in this paper achieve the robust performance of a desired error rejection function. Moreover, as expected, multi-rate controllers has the ability of outperforming their single-rate counterparts.
Inertial and Vision Sensor Based End-Effector Sensing and Control for Robot Manipulators
Authors: Cheng H. , Tomizuka M.
Published: February 2011

In the application of industrial robot manipulators, it is often desirable to obtain accurate position and velocity information regarding the end-effector. Estimations based on motor-side encoders alone are often inaccurate due to joint flexibilities and errors in the robot link kinematics. A vision based approach may also be insufficient due to its low sampling rate and image processing and transportation delay. However, with additional accelerometer measurements, a kinematic Kalman filter (KKF) can be formulated to estimate the end-effector motion accurately without encoder signals. The estimation results can be utilized for real time tracking control effectively. In this paper a multirate kinematic Kalman filter (KKF) scheme is formulated using vision and acceleration measurements from the end-effector. Estimations based on the scheme are utilized as feedback signals for tracking control. The effectiveness of the proposed approach is demonstrated by experiments on a single joint direct drive setup.
Self-Excited Oscillations in a System Model of the Human Thyroid
Authors: Gottlieb O. , Chipkin S. R. , Ioffe L. , Chait Y.
Published: February 2011

The thyroid, the largest gland in the endocrine system, secretes hormones that regulate homeostatic functions within the body and promote normal growth and development. Recently, a detailed computational model of the thyroid gland has been derived and used to explain clinical observations regarding the thyroid gland’s ability to maintain its hormonal secretion target in the face of uncertain dietary iodine intake levels. In this paper we probe deeper into the thyroid’s nonlinear dynamics. We first reduce the original model to an eight-order dynamical system, analytically determine that a Hopf mechanism governs the loss of stability of thyroid equilibrium, culminating with numerically obtained periodic limit-cycle behavior beyond the critical threshold. We numerically investigate the orbital stability of periodic thyroid dynamics via its harmonic perturbation and construct a bifurcation structure that includes both periodic and subharmonic mode-locked solutions embedded within a set of quasiperiodic tori. An increase of the perturbation parameter reveals a similar and structurally stable bifurcation structure. Thus, the analysis of our nonlinear thyroid model shows that the gland can exhibit both a stable equilibrium and periodic limit-cycle behavior which can lose its orbital stability due to small harmonic perturbations.
A Passive Dynamic Approach for Flapping-Wing Micro-Aerial Vehicle Control
Authors: Byl Katie
Published: February 2011

This article outlines a new control approach for flapping-wing micro-aerial vehicles (MAVs), inspired both by biological systems and by the need for lightweight actuation and control solutions. In our approach, the aerodynamic forces required for agile motions are achieved indirectly, by modifying passive impedance properties that couple motion of the power stroke to the angle of attack (AoA) of the wing. This strategy is theoretically appealing because it can exploit an invariant, cyclical power stroke, for efficiency, and because an impedance-adjusting strategy should also require lower bandwidth, weight, and power than direct, intra-wingbeat control of AoA. We examine the theoretical range of control torques and forces that can be achieved using this method and conclude that it is a plausible method of control. Our results demonstrate the potential of a passive dynamic design and control approach in reducing mechanical complexity, weight and power consumption of an MAV while achieving the aerodynamic forces required for the types of high-fidelity maneuvers that drive current interest in autonomous, flapping-wing robotics.
Tracking Control of Unmanned Surface Vehicles With Abkowitz Steering Model
Authors: Nataraj C. , Thimmaraya Ramesh
Published: February 2011

This paper is concerned with the tracking control of unmanned surface vehicles. Steering dynamics is modeled using nonlinear equations with three degrees of freedom following Abkowitz. Tracking control of this nonlinear system leads to the need to derive a control algorithm for linear error equations which have time-varying coefficients. Next, a control algorithm has been derived for this set of linear time-varying equations. Lyapunov transformations have been applied to transform the error equation into a canonical form. A desired closed-loop PD-spectrum and the desired right PD-modal matrix have been chosen and the resulting Sylvester equation has been solved to obtain a matrix of time-varying controller gains. This leads to the closed loop equations for controlling the ship steering of an unmanned ship. The controller algorithm is applied to the motion control of ships with parametric values from published reports. Several tracking trajectories have been generated with and without obstacles, and time-varying control has been investigated and presented. The control algorithm is shown to be quite effective for tracking of unmanned surface vehicles. Stability conditions are derived to ensure convergence. Present work in experimental verification is outlined.