bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal Energy Management of Hybrid Power System With Two-Scale Dynamic Programming
Authors: Zhang Lei , Li Yaoyu
Published: May 2012

Energy management is one of the main issues in operating the HPS, which needs to be optimized with respect to the current and future change in generation, demand, and market price, particularly for HPS with strong renewable penetration. Optimal energy management strategies such as dynamic programming (DP) may become significantly suboptimal under strong uncertainty in prediction of renewable generation and utility price. In order to reduce the impact of such uncertainties, a two-scale dynamic programming scheme is proposed in this study to optimize the operational benefit based on multi-scale prediction. First, a macro-scale dynamic programming (MASDP) is performed for the long term period, based on long term ahead prediction of hourly electricity price and wind energy (speed). The battery state-of-charge (SOC) is thus obtained as the macro-scale reference trajectory. The micro-scale dynamic programming (MISDP) is then applied with a short term interval, based on short term-hour ahead auto-regressive moving average (ARMA) prediction of hourly electricity price and wind energy. The nodal SOC values from the MASDP result are used as the terminal condition for the MISDP. The simulation results show that the proposed method can significantly decrease the operation cost, as compared with the single scale DP method.
Surface Deformations Enable High Pressure Operation of Axial Piston Pumps
Authors: Pelosi Matteo , Ivantysynova Monika
Published: May 2012

In this paper, a fully coupled fluid-structure interaction and thermal numerical model developed by the authors is used to demonstrate the impact of surface elastic deformations on the piston/cylinder fluid film thickness and on the overall axial piston pump rotating kit performance. The piston/cylinder interface is one of the most critical lubricating interfaces of axial piston machines. This interface fulfills simultaneously a bearing and sealing function under oscillating load conditions in a purely hydrodynamic regime. It represents one of the main sources of energy dissipation and it is therefore a key design element, determining axial piston machine efficiency. In the past years, the research group of the authors studied the impact of advanced micro surface design and fluid film thickness micro alteration in the piston/cylinder interface through extensive simulations and experiments. However, the numerical models used did not include the influence of surface elastic deformations, heat transfer and therefore material properties on the piston/cylinder interface behavior. Hence, the aim of this paper is to show the alterations on fluid film thickness and on the consequent coupled physical parameters due to the solid boundaries pressure and thermal surface elastic deformations. A simulation study considering two different material properties for the cylinder bores is performed, where a steel cylinder block and a steel cylinder block with brass bushings are separately studied. Piston/cylinder gap pressure field and coupled gap surface elastic deformations due to pressure and thermal loading are shown for the different materials. The impact of the different materials behavior on lubricating interface performance is discussed.
Turbocharger Map Reduction for Control-Oriented Modeling
Authors: Stricker Karla , Kocher Lyle , Koeberlein Ed , Van Alstine D. G. , Shaver Greg
Published: May 2012

The gas exchange process in a modern diesel engine is generally modeled using manufacturer-provided performance maps that describe mass flows through, and efficiencies of, the turbine and compressor. These maps are typically implemented as look-up tables requiring multiple interpolations based on pressure ratios across the turbine and compressor, as well as the turbocharger shaft speed. In the case of variable-geometry turbochargers, the nozzle position is also an input to these maps. This method of interpolating or extrapolating data is undesirable when modeling for estimation and control, and though there have been several previous efforts to reduce dependence on turbomachinery maps, many of these approaches are complex and not easily implemented in engine control systems. As such, the aim of this paper is to reduce turbocharger maps to analytical functions for models amenable to estimation and control.
Myoelectric Torque Control of an Active Transfemoral Prosthesis During Stair Ascent
Authors: Hoover Carl D. , Fite Kevin B. , Fulk George D. , Holmes Donald W.
Published: May 2012

This paper presents experimental results of a myoelectric impedance controller designed for reciprocal stair ascent with an active-knee powered transfemoral prosthesis. The controller is modeled from non-amputee (normal) motion capture data, estimating knee torque with a linear two-state (stance/swing) impedance control form that includes proportional myoelectric torque control. The normal gait model is characterized by small stiffness and damping in both stance and swing, a low angle set-point in stance, a high angle set-point in swing, and proportional myoelectric control in stance but not swing. Clinical tests with a single unilateral transfemoral amputee indicate good performance of the controller; however, subject feedback suggests a reduction in the extensive myoelectric torque parameter and the need for constant, balanced myoelectric torque parameters in both stance and swing. Average prosthesis knee joint kinetics from a stairwell test using the amputee-tuned controller compare favorably with non-amputee gait data.
Biosensor Based Video Game Control for Physically Disabled Gamers
Authors: Breugelmans Jeffrey , Lin Yingzi
Published: May 2012

PC-based video games are commonly controlled through a combination of pointing device and keyboard input. Although this conventional type of interface has a long history of successful implementation, a small group of people remains excluded due to accessibility issues. This is unfortunate, because virtual environment immersion can provide great benefits to people suffering from temporary or permanent physical disabilities. This work describes the development of a novel human-computer interface system that incorporates biosensors in order to replace conventional input devices. It will engage this group of overlooked users by addressing and eliminating the previously mentioned accessibility issues. In this system, the input from an eye-tracking device will be used to replace on-screen pointing, and a data-glove will be used to replace keyboard input for in-game navigation and interaction. It is expected that previously limiting physical conditions will be eliminated by the system’s effective, effortless, and pleasant interaction control implications.
Optimal LQ Transient Air-to-Fuel Ratio Control of an Internal Combustion Engine
Authors: Pace Stephen , Zhu Guoming G.
Published: May 2012

Most modern spark ignited (SI) internal combustion engines maintain their air-to-fuel ratio (AFR) at a desired level to maximize the three-way catalyst conversion efficiency and to extend its life. However, maintaining the engine AFR during its transient operation is quite challenging due to rapid changes of driver demands. Conventional transient AFR control is based upon the inverse dynamics of the engine port-fuel-injection well-wetting dynamics and the measured mass air flow rate. This paper develops a dynamic linear quadratic (LQ) tracking controller to regulate the AFR using a control oriented model of the wall wetting dynamics of a port fuel injector (PFI) and estimated transport delays of the airflow travel and throttle dynamics. The LQ tracking controller is designed to optimally track the measured airflow through the throttle during engine transients over a given time interval. The performance of the optimal LQ tracking controller was compared with the conventional inverse fueling dynamics through simulations and showed improvement over the baseline controller.
A Miniature and Low-Cost Robotic Fish for Ethorobotics Research and Engineering Education: I—Bioinspired Design
Authors: Kopman Vladislav , Porfiri Maurizio
Published: May 2012

The development of underwater biomimetic robots has recently become an active research topic due to their stealth, performance, and maneuverability. In this two-part paper, we present the system design and characterization of a multipurpose, miniature, bioinspired low-cost robotic fish implemented in a fun-science activity for pre-high school students at the New York Aquarium; the activity is aimed at igniting K-12 students’ interest in science, technology, engineering, and mathematics (STEM) and to attract them toward engineering careers. The robot features a servomotor-actuated modular caudal fin for selection of swimming modality and thrust optimization. The thrust produced by various caudal fin geometries is experimentally quantified, reported, and discussed. In addition to its applications in K-12 education, this robotics platform is utilized for several robot-live fish interaction studies, where the effect of robot leadership in fish shoals is investigated.
A Miniature and Low-Cost Robotic Fish for Ethorobotics Research and Engineering Education: Part II—STEM Outreach
Authors: Abaid Nicole , Kopman Vladislav , Porfiri Maurizio
Published: May 2012

Interactive robotics in formal and informal settings alike has been shown to effectively excite and educate learners at every level. In this second of two papers, we present the educational application of recently-developed biomimetic robotic fish for K-12 learning at the New York Aquarium focused on underwater robotics and marine science. We narrate the development, organization, and execution of an outreach program designed around these robotic fish to pique K-12 students’ interest in science, technology, engineering, and mathematics (STEM) and to attract them toward engineering careers. The activity offers an authentic engineering experience through bioinspired modification of the swimming robots informed by observation of the aquarium’s inhabitants. Student survey responses indicate the success of the activity in influencing the students’ perception of engineering. More specifically, the students showed an increased interest in STEM fields and found engineering to be a more accessible and exciting discipline after the activity.
Parameter-Dependent Identification of the Intake Manifold System Dynamics in Spark Ignition Engines Using LPV Methods
Authors: Zope Rohit A. , Mohammadpour Javad , Grigoriadis Karolos , Franchek Matthew , Wang Yue-Yun
Published: May 2012

Presented in this paper is a Recursive Least Squares (RLS) based algorithm for system identification of Linear Parameter-Varying (LPV) systems. An identification method based on the input-output representation of LPV systems is employed, where the coefficients of the model depend on external parameters assumed to be measurable in real-time. The identification problem is reduced to a problem of linear regression. Application of the proposed method to a quasi-LPV system developed from an intake manifold model of a spark ignition (SI) engine is demonstrated. Simulations performed using the GT-Power simulation tool and experiments performed on a 5.4-L V8 spark-ignition engine are used validate the accuracy of the proposed method.
Development of Vibration Loading Profiles for Accelerated Durability Tests of Ground Vehicles
Authors: Xu Ke , Wu Yan , Wu Qiong
Published: May 2012

The accelerated durability test can be achieved by using the GlyghWorks software through the process of Mission Profile and Test Synthesis. Mission profile comprises a number of load events that simulate the real world driving conditions, which contain dynamic information about the vehicle. Test Synthesis is accomplished with extracting the information on the frequency of the events expected in the service life. The challenge of accurately separating the time series signal that correlate the load events becomes essential in order to efficiently conduct the accelerated durability test analysis. In this paper, a method is developed for automatic event identification from a time series based on wavelet analysis, clustering, and Fourier analysis, which are applied respectively to denoise, cluster and refine the segmentation of respective events embedded in the time series signal. The identified events and their corresponding data are used to generate the accelerated durability testing profiles. A systematic approach of acceleration time series generation for the partial test based on the durability testing PSD profile will also be shown, and then the created loading profile can be directly applied as the driven profile in the lab test. Subsequently, method of validation process for the partial test will be introduced.
Optimal Control of a Gearshift With a Dual-Clutch Transmission
Authors: Szabo Tomas , Buchholz Michael , Dietmayer Klaus
Published: May 2012

This paper presents a model for a heavy duty truck powertrain test rig with a dual-clutch transmission. For this powertrain model, an LQR controller is designed to compute the torque profiles for performing powershifts while both clutches are slipping. Since most of the system states are not measurable, a Kalman-Bucy filter is implemented to estimate the states. The controller and estimation performance will be discussed in detail using both simulation and measurement results.
Toward Fluoroscopic Shape Reconstruction for Control of Steerable Medical Devices
Authors: Burgner Jessica , Herrell S. Duke , Webster Robert J.
Published: May 2012

Control of surgical continuum robot manipulators and steerable needles requires accurate real-time sensing of tip position and/or shaft shape. Medical image feedback provides the most straightforward and widely available method of measuring device and clinical target positions and shapes during insertion or tissue manipulation. In this paper we present a method for automatic robot/needle curve segmentation from fluoroscopic images, as well as a method for 3D reconstruction of the curve using biplane fluoroscopy images.
Ritz Model of a Lead-Acid Battery With Application to Electric Locomotives
Authors: Shen Zheng , Gou Jun , Rahn Christopher D. , Wang Chao-Yang
Published: May 2012

Pb-Acid batteries are excellent candidates for hybrid and electric locomotive, primarily due to their low cost. Model-based design, estimation, and control of a Pb-Acid energy storage system for a locomotive requires the development of efficient and accurate models. This paper presents a first principles model based on the fundamental governing equations of species and charge conservation for a Pb-Acid cell. The governing equations are discretized using a Ritz method to produce a low order and numerically efficient model that simulates over 20 times faster than CFD. The Ritz model outputs variables of interest such as voltage and internal potential, current, and concentration distributions in response to the current input. The Ritz model can be cast in state variable form, making it amenable to systems analysis using Matlab and model-based estimator and controller design. The accuracy of the Ritz model decreases with increasing charge/discharge rate, low or high State of Charge, and increasing charge/discharge time due to linearization of the Butler-Volmer equation, linearization of the open circuit voltage, and constant porosity assumptions, respectively. Finally, the time constant during charge is significantly different than that during discharge due to different specific areas, motivating the use of a time-varying model.
Disturbance Rejection Helps Modulate the p53 Oscillation
Authors: Shin Yong-Jun , Lipkin Steven M. , Hencey Brandon , Shen Xiling
Published: May 2012

Designing a system that adequately processes the input and that rejects the effects of disturbance is a central theme in feedback control theory. In this paper, we use the concept of “disturbance rejection” to analyze the oscillatory behavior of p53, a well-known tumor suppressor protein. Our analysis reveals that the p53 oscillation is not completely dictated by the p53-MDM2 negative feedback loop—it is also modulated by periodic DNA repair-related fluctuations. According to our disturbance rejection model, the feedback loop normally filters the effects of noise and fluctuations on p53, but upon DNA damage, it stops performing the filtering function so that DNA repair-related fluctuations can modulate the p53 oscillation. Our analysis suggests that the overexpression of MDM2, observed in many types of cancer, can make the feedback mechanism less responsive to the modulating signals after DNA damage occurs.
A Model of Self-Propelled Particles Coordinating Under External Leadership
Authors: Aureli Matteo , Porfiri Maurizio
Published: May 2012

In this paper, we investigate the emergence of organization patterns in a group of self-propelled particles in the presence of a mobile external leader particle. Particle-to-particle interactions and particle-to-leader interactions are described through biologically-relevant pairwise potentials. Simulation results in two dimensions reveal the existence of a variety of long run particle aggregation states, including highly polarized tracking of the leader and coherent milling about it. Transition between aggregation states is triggered by the interplay of particle energy, group size, interaction strength, and leader mobility. These findings provide insights in the structure and organization of biological groups under the influence of external aggregation devices, environmental stimuli, or trained individuals taking the lead.
Optimal Sliding Mode Control for a Class of Underactuated Nonlinear Systems
Authors: Ghorbanian Parham , Nersesov Sergey G. , Ashrafiuon Hashem
Published: May 2012

In this paper, a general framework that provides sufficient conditions for asymptotic stabilization of underactuated nonlinear systems using an optimal sliding mode control in the presence of system uncertainties is presented. A performance objective is used to optimally select the parameters of the sliding mode control surfaces subject to state and input constraints. It is shown that the closed-loop system trajectories reach the optimal sliding surfaces in finite time and a constructive methodology to determine exponential stability of the closed-loop system on the sliding surfaces is developed which ensures asymptotic stability of the overall closed-loop system. The framework further provides the basis to determine an estimate of the domain of attraction for the closed-loop system with uncertainties. The results developed in this work are experimentally validated using a linear inverted pendulum testbed which show a good match between the actual domain of attraction of the upward equilibrium state and its analytical estimate.
A New Method for Determining Melt Front Velocity Through Temperature Measurement
Authors: Gao Robert X. , Fan Zhaoyan , Asadizanjani Navid , Kazmer David
Published: May 2012

Online measurement of pressure, temperature, velocity, and viscosity of polymer melt within the injection mold is key to improving process control for quality assurance in injection molding. A multivariate sensing method has been introduced to enable simultaneous determination of the four parameters in injection molding using one single sensor package. Comparing with the method of measuring different physical parameters using separate sensors, the new method is advantageous in terms of system miniaturization and energy efficiency. This paper addresses the aspect of polymer melt velocity sensing based on the melt temperature measured by an Infrared (IR) sensing element integrated within the sensor package. From the Stephan-Boltzmann model, an analytical relationship between the melt front velocity and the ramping rate of the IR detector voltage output has been established. Using a Finite Element (FE) model, the process of polymer melt flowing over the IR sensor lens has been simulated. The result shows that the melt front velocity can be determined within an error of ± 0.25%, under a broad range of melt temperature and IR detector diameters. The result is experimentally confirmed by temperature measurement in a realistic injection molding machine instrumented with a reference IR sensor.
Wind Turbine Torque and Wind Speed Estimation
Authors: Villanueva J. , Alvarez-Icaza L.
Published: May 2012

An adaptive-observer to estimate both the parameters of a new model of the mechanical torque in a wind turbine and the wind velocity is proposed. The model is based in a relative velocity between the wind speed and blades of turbine. Results of torque estimation are compared with those obtained from a heuristic model, commonly used in the literature, showing very good agreement.
Adaptive Hybrid Control for Rotationally Oscillating Drill (Ros-Drill©), Using a Low-Resolution Sensor
Authors: Zhang Zhenyu , Diaz Jhon , Olgac Nejat
Published: May 2012

A novel hybrid (i.e., discrete/continuous) control system is studied on a cellular microinjector technology called the Ros-Drill© (Rotationally Oscillating Drill). Ros-Drill© is developed primarily for ICSI (Intra-Cytoplasmic Sperm Injection). It is an inexpensive set-up, which creates high-frequency rotational oscillations at the tip of an injection pipette tracking a harmonic motion profile. These rotational oscillations enable the pipette to drill into cell membranes with minimum biological damage. Such a motion control procedure presents no particular difficulty when it uses sufficiently precise motion sensors. However, size, costs and accessibility of technology on hardware components may severely constrain the sensory capabilities. Then the trajectory tracking is adversely affected. In this paper we handle such a practical case, and present a novel adaptive-hybrid control logic to overcome the hurdles. The control is implemented using a commonly available microcontroller and extremely low-resolution position measurements. First, the continuous control system is analyzed and designed. Then, an adaptive, robust and optimal PID (proportional-integral-derivative) control strategy is performed. We demonstrate via simulations and experiments that the tracking of the harmonic rotational motion is achieved with desirable fidelity.
Design and Control of a Compact and Flexible Pneumatic Artificial Muscle Actuation System: Part Two—Robust Control
Authors: Wu Sai-Kit , Waycaster Garrett , Driver Tad , Shen Xiangrong
Published: May 2012

A robust control approach is presented in this part of the paper, which provides an effective servo control for the novel PAM actuation system presented in Part I. Control of PAM actuation systems is generally considered as a challenging topic, due primarily to the highly nonlinear nature of such system. With the introduction of new design features (variable-radius pulley and spring-return mechanism), the new PAM actuation system involves additional nonlinearities (e.g. the nonlinear relationship between the joint angle and the actuator length), which further increasing the control difficulty. To address this issue, a nonlinear model based approach is developed. The foundation of this approach is a dynamic model of the new actuation system, which covers the major nonlinear processes in the system, including the load dynamics, force generation from internal pressure, pressure dynamics, and mass flow regulation with servo valve. Based on this nonlinear model, a sliding mode control approach is developed, which provides a robust control of the joint motion in the presence of model uncertainties and disturbances. This control was implemented on an experimental setup, and the effectiveness of the controller demonstrated by sinusoidal tracking at different frequencies.
Towards the Development of a Tendon-Driven Neurosurgical Robot
Authors: Ho Mingyen , Desai Jaydev P.
Published: May 2012

Brain tumors are among the most feared complications of cancer and their treatment is challenging due to the lack of good continuous imaging modality during the procedure and the inability to remove the complete tumor due to obstructions. A highly dexterous, small cross-section robot is being developed to overcome these limitations. The robot is being designed to remove the tumor which is outside the direct “line-of-sight” of the physician. In this paper, we report the design of a Minimally Invasive Neurosurgical Intracranial Robot (MINIR) using a tendon-driven mechanism. In the current prototype presented in this paper, the actuators for actuating the robot are not MRI compatible. The primary goal of this paper is to evaluate the performance of the robot motion and not the MRI compatibility of the entire system. The robot contains four links and four revolute joints. Pulleys and cables are put inside the robot to make the robot compact. The four revolute joints are placed orthogonally to have out-of-plane motion capability and can be controlled independently.
Optimal Efficiency-Power Tradeoff for an Air Motor/Compressor With Volume Varying Heat Transfer Capability
Authors: Rice Andrew T. , Li Perry Y.
Published: May 2012

This paper presents the pressure-volume trajectories that yield the optimal tradeoff between efficiency and power during the compression and expansion of air. These results could benefit applications such as compressed air energy storage where both high efficiency and power density are required. Earlier work established solutions for the simple case in which hA, the product of the heat transfer coefficient and heat transfer surface area, is constant. This paper extends that analysis by allowing hA to vary with air volume. Solutions to the constrained, non-linear optimization problem are developed utilizing the method of Lagrange multipliers and Karush-Kuhn-Tucker (KKT) conditions. It is found that the optimal trajectory takes the form “fast-slow-fast” where the fast stages are adiabatic and the temperature change during the slow stage is proportional to the inverse root of the hA product. A case study predicts a 60% improvement in power over the constant-hA solution when both trajectories are run at 90% efficiency and hA = hA(V). Compared to linear- and sinusoidal-shaped trajectories, also at 90% efficiency, power gains are expected to be in the range of 500–1500%.
Model-Based Hierarchical Optimal Control Design for HVAC Systems
Authors: Maasoumy Mehdi , Pinto Alessandro , Sangiovanni-Vincentelli Alberto
Published: May 2012

A hierarchical control architecture for balancing comfort and energy consumption in buildings is presented. The control design is based on a simplified, yet accurate model of the temperature within each room of the building. The model is validated against real measurements. The control architecture comprises a first level that regulates low level quantities such as air flow, and a second level that balances comfort (i.e. distance between the desired and actual temperature) and energy consumption (i.e. total energy consumed for the required level of comfort). We show the effectiveness of our approach by simulation using validated models.
Online Adaptive Model Based Fault Detection, Isolation and Estimation Method
Authors: Gupta Aniket , Grigoriadis Karolos , Franchek Matthew , Smith Daniel J.
Published: May 2012

In the present study a methodology to perform fault detection, isolation and estimation is proposed that is based on adaptive model based techniques. Fault detection and diagnostics is performed by comparing the coefficients of healthy system model with that of adapted online coefficients. This approach is shown to be robust to modeling errors, sensor noise and process variability. The proposed approach is applied to FTP-75 cycle simulation data of exhaust gas recircultaion (EGR) faults and is shown to effectively perform fault detection and diagnosis.
Facilitating Joint Chaos and Fractal Analysis of Biosignals Through Nonlinear Adaptive Filtering
Authors: Gao Jianbo , Hu Jing , Tung Wen-wen
Published: May 2012

Chaos and random fractal theories are among the most important for fully characterizing nonlinear dynamics of complicated multiscale biosignals. Chaos analysis requires that signals be relatively noise-free and stationary, while fractal analysis demands signals to be non-rhythmic and scale-free. To facilitate joint chaos and fractal analysis of biosignals, we report an adaptive multiscale decomposition algorithm, which: (1) can readily remove nonstationarities from the signal, (2) can more effectively reduce noise in the signals than linear filters, wavelet denoising, and chaos-based noise reduction schemes; (3) can readily decompose a multiscale biosignal into a series of intrinsically bandlimited functions; (4) offers a new formulation of fractal and multifractal analysis that is better than the popular detrended fluctuation analysis when a biosignal contains a strong oscillatory component. The effectiveness of the approach is demonstrated by applying it to classify EEGs for the purpose of detecting epileptic seizures.
Multiscale Analysis of Biological Signals
Authors: Gao Jianbo , Hu Jing , Tung Wen-wen
Published: May 2012

Complex systems often generate highly nonstationary and multiscale signals, due to nonlinear and stochastic interactions among their component systems and hierarchical regulations imposed by the operating environments. The further advances in the fields of life sciences, systems biology, nano-sciences, information systems, and physical sciences, have made it increasingly important to develop complexity measures that incorporate the concept of scale explicitly, so that different behaviors of the signals on varying scales can be simultaneously characterized by the same scale-dependent measure. Here, we propose such a measure, the scale-dependent Lyapunov exponent (SDLE), and develop a unified theory of multiscale analysis of complex data. We show that the SDLE can readily characterize low-dimensional chaos and random 1/fα processes, as well as accurately detect epileptic seizures from EEG data and distinguish healthy subjects from patients with congestive heart failure from heart rate variability (HRV) data. More importantly, our analyses of EEG and HRV data illustrate that commonly used complexity measures from information theory, chaos theory, and random fractal theory can be related to the values of the SDLE at specific scales, and useful information on the structured components of the data is also embodied by the SDLE.
Physics-Based Control Oriented Mean Value Model for Diesel Combustion Process With EGR Sensitivity
Authors: Lee Byungchan , Jung Dohoy , Kim Yong-Wha
Published: May 2012

A Physics-based mean value model that predicts engine combustion, heat transfer, gas exchange, and friction loss has been developed. The model is developed starting from the thermodynamic principles of an ideal gas standard limited pressure cycle concept. The idealized assumptions that are typically used in a limited pressure cycle concept are relieved to enhance the fidelity of the model by introducing variables that account for the in-cylinder heat transfer and the combustion characteristics that change under varying EGR rate as well as the engine speed and load while minimal number of empirical correlations are used to ensure the compactness and flexibility of the physics-based mean value model. The model is calibrated and validated with the simulation results from a detailed GT-Power® engine model previously calibrated with experimental results from a Ford 6.7 liter Diesel engine. The comparison shows good agreement between the results from the mean value model and the GT-Power® model. The mean value model developed in this study is a flexible simulation tool that provides excellent computational efficiency without sacrificing critical physical details of the Diesel combustion process required by the control design development.
Combustion Phasing Variation Reduction for Late-Phasing HCCI Through Cycle-to-Cycle Pilot Injection Timing Control
Authors: Jungkunz Adam F. , Ravi Nikhil , Liao Hsien-Hsin , Gerdes J. Christian
Published: May 2012

Late-phasing homogeneous charge compression ignition (HCCI) operating conditions have the potential to expand the useful operating range of HCCI. However, these conditions exhibit significant variation in combustion timing and work output from one cycle to the next. Cyclic variations in the combustion timing of HCCI combustion at late-phasing operating conditions can be removed through the use of cycle-to-cycle control of pilot fuel injection timing. A nonlinear, discrete-time model of the recompression HCCI process captures the oscillations in late-phasing HCCI; when this model is linearized, it represents these dynamics as a pole on the negative real-axis. A simple lag compensator eliminates the oscillations in combustion phasing and drastically improves the operability of late-phasing HCCI. in both simulation and experiment.
Spatial Prediction With Mobile Sensor Networks Using Gaussian Process Regression Based on Gaussian Markov Random Fields
Authors: Xu Yunfei , Choi Jongeun
Published: May 2012

In this paper, a new class of Gaussian processes is proposed for resource-constrained mobile sensor networks. Such a Gaussian process builds on a GMRF with respect to a proximity graph over a surveillance region. The main advantages of using this class of Gaussian processes over standard Gaussian processes defined by mean and covariance functions are its numerical efficiency and scalability due to its built-in GMRF and its capability of representing a wide range of non-stationary physical processes. The formulas for Bayesian posterior predictive statistics such as prediction mean and variance are derived and a sequential field prediction algorithm is provided for sequentially sampled observations. For a special case using compactly supported kernels, we propose a distributed algorithm to implement field prediction by correctly fusing all observations in Bayesian statistics. Simulation results illustrate the effectiveness of our approach.
Modeling and Validation of Free-Piston Stirling Engines Using Impedance Controlled Hardware-in-the-Loop
Authors: Hofacker Mark E. , Tucker John M. , Barth Eric J.
Published: May 2012

This paper describes a method of energetically modeling a free-piston Stirling engine. This model is compared to a lower order Schmidt model, and both models are linearized from nonlinear continuous form and cast into closed-loop state space models. To validate the linear models, an experimental apparatus to simulate the performance of different engines was constructed using linear actuators, sensors, and a free-piston Stirling engine. The behavior of the experimental apparatus was compared to the behavior predicted by the linear models. The operating characteristics of the experimental apparatus are compared to the dominant poles of the closed loop models. Relations are described between the imaginary component of the dominant poles and the operating frequency of the engine and between the real component and the ability of the engine to enter sustained oscillation.
A Control Loop Structure Based on Singular Value Decomposition for Input-Coupled Systems
Authors: Winck Ryder C. , Book Wayne J.
Published: May 2012

This paper introduces a control structure based on the singular value decomposition (SVD) to control multiple subsystems with reduced inputs. The SVD System permits simultaneous, dependent control of sets of subsystems coupled by a row-column input design. The use of the SVD differs from previous applications because it is used to obtain a low-rank approximation of desired inputs. The row-column system allows many actuators to be controlled by a few inputs. Current control methods using the row-column system rely on scheduling techniques that permit independent actuator control but are too slow for many applications. The inspiration for this new control construct is a pin array human machine interface, called Digital Clay. Some useful properties of the SVD will be discussed and the SVD System will be described and demonstrated in a simulation of Digital Clay.
Modeling Ranges of Cyclic Variability for HCCI Ignition Timing Control
Authors: Shahbakhti Mahdi , Ghazimirsaied Ahmad , Koch Charles Robert
Published: May 2012

The probability distribution shape of the ignition timing ensemble allows detection of unstable operation near misfire in Homogeneous Charge Compression Ignition (HCCI) engines. The acceptable range of cyclic variation in HCCI combustion timing is determined by linking the experimental measurements with the shape factors of Generalized Extreme Value (GEV) probability distribution. A combined physical-statistical model is incorporated to analyze the range of cyclic variability in CA50 (crank angle of 50% mass fraction fuel burnt) for two single-cylinder engines. The model is validated with the experimental data at 227 operating points with five different Primary Reference Fuels (PRF). Good agreement between simulation and the experiment with an average error of 0.36 crank angle degree for predicting standard deviation of CA50 is obtained. Low, medium and high cyclic variability zones are identified as a function of intake manifold pressure, equivalence ratio, and intake manifold temperature. This information can be integrated into the design of an engine controller strategy to maintain acceptable levels of cyclic variation during a commanded engine load change.
Comparison of Optimal Supervisory Control Strategies for a Series Plug-In Hybrid Electric Vehicle Powertrain
Authors: Patil Rakesh , Filipi Zoran , Fathy Hosam
Published: May 2012

This paper uses dynamic programming to compare the optimal fuel and electricity costs associated with two supervisory control strategies from the plug-in hybrid electric vehicle (PHEV) literature. One strategy blends fuel and electricity for propulsion throughout the useful range of battery state of charge (SOC), while the second strategy switches from all-electric to blended operation at a predefined SOC threshold. Both strategies are optimized for a series PHEV powertrain using deterministic dynamic programming (DDP) to ensure a fair comparison. The DDP algorithm is implemented in a novel manner using a backward-looking powertrain model instead of forward-looking models used in previous research. The paper’s primary conclusion is that there is no significant difference in the performance of the two control strategies for the series PHEV considered. This result contrasts sharply with previous results for parallel and power-split PHEVs, and is examined for different relative fuel and electricity prices and trip lengths.
Integrator Leakage for Limit Cycle Suppression in Servo Mechanisms With Stiction
Authors: Jeon Soo
Published: May 2012

This paper reports quantitative answers to two questions regarding the limit cycle behavior arising from the servo mechanisms with stiction under the positional PID (Proportional-Integral-Derivative) control. The first question is, how large the magnitude of the limit cycle is for a given value of stiction force. The second one is how we should modify the PID controller to avoid this limit cycle with minimal degradation in the serve performance. The main approach is based on understanding key algebraic properties of the state trajectory. As a result, a simple bisection algorithm has been devised to compute the exact magnitude of the periodic solution for a given value of stiction. A direct extension of this algorithm enables us to find the minimum value of the integrator leakage to avoid the limit cycle. A numerical example demonstrates the main results.
Optimal Energy Management for a Hybrid Vehicle Using Neuro-Dynamic Programming to Consider Transient Engine Operation
Authors: Johri Rajit , Salvi Ashwin , Filipi Zoran
Published: May 2012

This paper proposes a self-learning approach to develop optimal power management with multiple objectives, e.g. to minimize fuel consumption and transient engine-out NOx and particulate matter emission for a series hydraulic hybrid vehicle. Addressing multiple objectives is particularly relevant in the case of a diesel powered hydraulic hybrid since it has been shown that managing engine transients can significantly reduce real-world emissions. The problem is formulated as an infinite time horizon stochastic sequential decision making/markovian problem. The problem is computationally intractable by conventional Dynamic programming due to large number of states and complex modeling issues. Therefore, the paper proposes an online self-learning neural controller based on the fundamental principles of Neuro-Dynamic Programming (NDP) and reinforcement learning. The controller learns from its interactions with the environment and improves its performance over time. The controller tries to minimize multiple objectives and continues to evolve until a global solution is achieved. The control law is a stationary full state feedback based on 5 states and can be directly implemented. The controller performance is then evaluated in the Engine-in-the-Loop (EIL) facility.
Nonlinear Control of Variable Speed Wind Turbines With Switching Across Operating Regimes
Authors: Das Tuhin , Semrau Greg , Rimkus Sigitas
Published: May 2012

One of the key control problems associated with variable speed wind turbine systems is maximization of energy extraction when operating below the rated wind speed and power regulation when operating above the rated wind speed. In this paper, we approach these problems from a nonlinear systems perspective. For below rated wind speeds we adopt existing work appearing in the literature and provide further insight into the characteristics of the resulting equilibrium points of the closed-loop system. For above rated wind speeds, we propose a nonlinear controller and analyze the stability property of the resulting equilibria. We also propose a method for switching between the two operating regimes that ensures continuity of control input at the transition point. The control laws are verified using a wind turbine model with a standard turbulent wind speed profile that spans both operating regimes.
An Adaptive Block Backstepping Control Design for Functional Electrical Stimulation of Agonist-Antagonist Muscles
Authors: Koo Bonsung , Leonessa Alexander
Published: May 2012

In this paper, an adaptive block backstepping controller is developed for stimulation of agonist-antagonist muscles by using Functional Electrical Stimulation (FES). FES is an alternative method that stimulates a paralyzed muscle in lieu of inactive motor neurons, which was first implemented in the 1960s ([1]). However, many challenges need to be addressed before clinical trials with Spinal Cord Injury (SCI) patients can be performed, which include designing a controller, modeling muscles, developing interface equipment, just to mention a few. To contribute to the FES control field, a nonlinear controller and its evaluation through a computer simulation are presented.
Force Control of Pneumatic Actuators Utilizing a New Pressure Estimation Technique
Authors: Driver Tad , Shen Xiangrong
Published: May 2012

In this paper, a new method of estimating the pressures needed to control the force output of a pneumatic cylinder is presented. A sliding mode force controller, encapsulating the dynamics of the system, is developed in order to implement and validate the pressure estimation. Experiments were conducted in order to measure the accuracy of the pressure estimation against that of the actual pressures. The results presented show that the estimated pressures accurately represent the actual pressures of the system.
A Moving Magnet Actuator for Large Range Nanopositioning
Authors: Parmar G. , Hiemstra D. B. , Chen Y. , Awtar S.
Published: May 2012

In this paper, we present the design, fabrication, and testing of a moving magnet actuator (MMA) for large range (∼10mm) nanopositioning. MMAs are direct-drive, single-phase electromagnetic linear actuators that provide frictionless and backlash-free motion. These qualities, along with an adequate motion range, make MMAs promising candidates for large range nanopositioning. In this work, we identify actuator- and system-level performance criteria and associated design tradeoffs, and use this knowledge to systematically and concurrently design an MMA and a double parallelogram flexure bearing. The resulting actuator provides a force output per unit square root power of 4.56N/W, better than 9% force uniformity with respect to stroke, and a low moving mass of 106g. An integrated thermal management system is also incorporated as part of the actuator in order to mitigate the heat dissipated from the MMA coils. The overall single-axis motion system was fabricated and tested to demonstrate a 36Hz open-loop bandwidth and less than 4nm (RMS) steady-state positioning noise over a 10mm motion range. Preliminary closed-loop design and testing highlight the potential of the proposed actuator in nanopositioning.
Active Vibration Control of Gantry Structures Using PZT Actuators
Authors: Naranjo Walter , Fajardo William J. , Motato Eliot
Published: May 2012

In this paper the Active Vibration Control (AVC) of a three-story gantry type structure is designed. AVC is a viable solution to decrease drift (relative displacement between the slabs) in civil structures under seismic excitation. The structure under consideration is composed by six individual gantries. Dynamic models of these individual components are obtained using classical structural dynamic methods and include a reduction of its degree of freedom (DOF). The complete model of the three-story structure is obtained assuming a rigid diaphragm behavior of the slabs. This model is a multi-input, multi-output linear ordinary differential equation (ODE) including nine DOF. The obtained ODE equation is transformed to its equivalent multi-input MIMO state space realization. The state space format is the require representation to easily apply the proposed LQR, LQG and H∞ control techniques. In addition, this work considers the possible location of the PZT actuators within the structure. Real seismic data were used to test the system performance. The controlled system response shows a substantial improvement when compared to the non-controlled structure behavior.
WCPG: A Central Pattern Generator for Legged Robots Based on Workspace Intentions
Authors: Barasuol Victor , De Negri Victor Juliano , De Pieri Edson Roberto
Published: May 2012

In this paper it is proposed a central pattern generator (CPG) based on workspace intentions, where the parameters of modulation have physical meaning and the walking can be adapted to overcome irregular terrains by changing few parameters. The walking features are independently modulated since there is no coupling relationship among WCPG parameters. Simulation results are presented to demonstrate the WCPG performance for a simplified quadruped robot model in different terrains.
Dynamic Simulation of Blood Flow Effects on Flexible Manipulators During Intra-Cardiac Procedures on the Beating Heart
Authors: Salimi A. , Mohammadpour J. , Grigoriadis K. , Tsekos N. V.
Published: May 2012

In this paper, we develop a numerical mixed flexible-rigid body model to take into account the effects of the external disturbances acting on a flexible manipulator secondary to the oscillatory transmitral blood flow in the left ventricle. The manipulator is made of a flexible rubber-like material to further extend the surgical robotic-based catheters’ degrees of freedom and steer-ability in beating-heart prosthetic aortic valve implantation procedure. Along with the developed numerical model, a detailed description of the catheter’s mechanical architecture and the actuation system is also provided. Necessity of employing such a model for the designed system is clearly justified using simulation studies.