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Thermal energy storage (TES) devices use phase change materials (PCMs) to store and release thermal energy. Control-oriented models are needed to predict the behavior of TES devices and experimental validation is necessary to demonstrate the predictive capabilities of these models. This paper presents an experimental validation of a switched moving boundary (MB) approach for modeling TES devices, where the dynamics of the device are captured with fewer states than traditional models. A graph-based modeling approach is used to model heat flow, while the moving boundary captures the time-varying liquid and solid regions of the TES. The model uses a finite state machine (FSM) to switch between four modes of operation based on the state-of-charge (SOC) of the TES. Results show that the switched MB approach has similar accuracy and lower computational cost compared to traditional modeling approaches when predicting the SOC of an experimental TES device. [ABSTRACT FROM AUTHOR]

This study investigates the flame dynamics of lean premixed kerosene combustion for two different degrees of fuel-air premixing using a swirl stabilized burner with an axially movable twin fluid fuel injection nozzle. Thermal power, equivalence ratio, and atomizing air mass flow are varied systematically for both nozzle positions investigated. Measurements of the droplet size distribution at the nozzle exit are provided for all operation points. NOx emission measurements and OH*-chemiluminescence flame images show that stationary combustion characteristics significantly change with the nozzle position. Flame Transfer Functions (FTFs) are presented and interpreted for all operation points. The FTFs for the two configurations differ most in the low frequency range where the influence of the droplet dynamics is expected to be highest. For both configurations, a change in thermal power does not affect droplet size, flame shape, NOx emissions, and FTF. The observed trends in response to changes in equivalence ratio and atomizing air mass flow are opposite for both configurations. NOx emissions and flame shape are independent of the atomization air mass flow in the highly premixed configuration but not in the partially premixed configuration. In contrast to this, the FTF is affected by changes of the atomization air mass flow in both configurations, but again the trends are opposite. The observed trends for the highly premixed configuration are modeled and reproduced by a change in the phase relation between the equivalence ratio fluctuations and other instability driving mechanisms. [ABSTRACT FROM AUTHOR]

This work concerns the numerical modeling of geometric nonlinear vibrations of slender structures in rotation using an original reduced order model based on the use of dual modes along with the implicit condensation method. This approach is an improvement of the classical ICE method in the sense that the membrane stretching effect is taken into account in the dynamic resolution. The dynamics equations are first presented and the construction of the reduced order model (ROM) is then proposed. The second part of the paper deals with numerical applications using the finite element method, first for a three-dimensional cantilever beam, then for an Ultra-High Bypass Ratio (UHBR) fan blade subject to aerodynamic loads. In the applications considered, the proposed method predicts more accurately the geometrically nonlinear behavior than the ICE method. [ABSTRACT FROM AUTHOR]

Distributed combustion systems have shown the potential to reduce emissions as well as increase load and fuel flexibility. A characteristic feature of such systems is a reacting jet in crossflow, which exhibits complex vortical structures. In this paper, a generic combustion chamber with elliptic reacting jets in crossflow is examined, operating under lean-premixed conditions at elevated pressure and exhibiting high-frequency transverse mode shapes. It can be seen that depending on the orientation of the elliptical shape of the jet to the crossflow, thermoacoustic modes can be suppressed. A multidimensional fast Fourier transform shows that low aspect ratios (major axis of the jet aligned with the crossflow) result in the mixed 1L1T mode of first longitudinal and first transverse structure, while this mode disappears at high aspect ratios. To get a more detailed insight into the different vortex systems of the various aspect ratios, dynamic mode decomposition is applied. This modal decomposition technique reveals for low aspect ratios a shear layer mode that oscillates at a frequency close to the acoustic mixed mode. For this configuration, a mode representing a flapping motion is also identified. For high aspect ratios, the shear layer vortex increases its frequency and a higher-frequent mode appears in the acoustic spectrum. [ABSTRACT FROM AUTHOR]

The analysis of the structural dynamics of multistage cyclic structures as linked components is required to model the interstage coupling. In turbomachinery, this can result in a collaboration between different compressor or turbine stages. This paper investigates the coupling between two rear drum blade integrated disk stages of an axial compressor to support the mechanical design process. Considering the vibration modeshapes of a multistage system, different components may coparticipate in the dynamics. For this reason, criteria to identify the modes affected by the coupling and to quantify this coupling are defined. This allows to distinguish between modes with interstage coupling, requiring the multistage system for their description, and uncoupled modes, involving a single stage. In addition, it is of interest to research methods to reduce the impact of the coupling on the vibrating system without drastically altering the geometry of the components. The vibration analyses of a two-stage compressor generalized geometry, representative of a compressor rear drum blisk, are presented as a study case. The use of a reducing method allows to describe the behavior of the nominal multistage system with a computationally efficient technique, enabling a parametric analysis of the stages' coupling. The investigation considers the effect of a set of geometrical and mechanical parameters on the dynamics, identifying the driving parameters of the coupled vibration characteristics. [ABSTRACT FROM AUTHOR]

A lumped-parameter dynamic performance model for a single-spool turbojet engine is presented in this paper. This model can handle pre and poststall transients under forward and reverse-flow conditions. The inter-component volume technique is employed instead of the standard matching technique to be able to handle high-frequency transients and reverse-flow conditions. Inspired by Greitzer's lumped-parameter surge model, momentum (duct) and volume elements are placed within the flow path to handle surge dynamics. Compressor and turbine maps are extended to low-flow and reverse-flow regions using a combination of the guidelines presented by Kurzke, the cubic axisymmetric characteristics of Moore and Greitzer, and a quadratic function guess for in-stall characteristics. Combustor efficiency, stability limits, and delay are taken from the literature. Poststall behavior of the model is validated using the data available in the literature for a Rolls-Royce Viper engine. A good match is observed with a correct prediction of poststall behaviors, which transition from surge after locked stall to multiple surge cycles around 80% speed and multiple surge cycles to surge after flameout around 95% speed. The effects of different modeling choices and modeling parameters on the obtained results are discussed. The produced model can be calibrated for a specific engine with surge tests, and it can be used for hard-to-test scenarios like surge after shaft breakage. Different surge/stall-causing events, such as fuel spiking, in-bleeding, and shaft breakage, are simulated to see the capabilities of the model. [ABSTRACT FROM AUTHOR]

We present a physics-inspired input/output predictor of lithium-ion batteries (LiBs) for online state-of-charge (SOC) prediction. The complex electrochemical behavior of batteries results in nonlinear and high-dimensional dynamics. Accurate SOC prediction is paramount for increased performance, improved operational safety, and extended longevity of LiBs. The battery's internal parameters are cell-dependent and change with operating conditions and battery health variations. We present a data-driven solution to discover governing equations pertaining to SOC dynamics from battery operando measurements. Our approach relaxes the need for detailed knowledge of the battery's composition while maintaining prediction fidelity. The predictor consists of a library of candidate terms and a set of coefficients found via a sparsity-promoting algorithm. The library was enhanced with explicit physics-inspired terms to improve the predictor's interpretability and generalizability. Further, we developed a Monte Carlo search of additional nonlinear terms to efficiently explore the high-dimensional search space and improve the characterization of highly nonlinear behaviors. Also, we developed a hyperparameter autotuning approach for identifying optimal coefficients that balance accuracy and complexity. The resulting SOC predictor achieved high predictive performance scores (RMSE) of 2.2 × 10-6 and 4.8 × 10-4, respectively, for training and validation on experimental results corresponding to a stochastic drive cycle. Furthermore, the predictor achieved an RMSE of 8.5 × 10-4 on unseen battery measurements corresponding to the standard US06 drive cycle, further showcasing the adaptability of the predictor and the enhanced modeling approach to new conditions. [ABSTRACT FROM AUTHOR]

Latent thermal energy storage (TES) devices could enable advances in many thermal management applications, including peak load shifting for reducing energy demand and cost of HVAC or providing supplemental heat rejection in transient thermal management systems. However, real-time feedback control of such devices is currently limited by the absence of suitable state of charge estimation techniques, given the nonlinearities associated with phase change dynamics. In this paper, we design and experimentally validate a state-dependent Riccati equation (SDRE) filter for state of charge estimation in a phase change material (PCM)-based TES device integrated into a single-phase thermal-fluid loop. The advantage of the SDRE filter is that it does not require linearization of the nonlinear finite volume model; instead, it uses a linear parameter-varying system model which can be quickly derived using graph-based methods. We leverage graph-based methods to prove that the system model is uniformly detectable, guaranteeing that the state estimates are bounded. Using measurements from five thermocouples embedded in the PCM of the TES and two thermocouples measuring the fluid temperature at the inlet and outlet of the device, the state estimator uses a reduced-order finite volume model to determine the temperature distribution inside the PCM and in turn, the state of charge of the device. We demonstrate the state estimator in simulation and on experimental data collected from a thermal management system testbed to show that the state estimation error converges near zero and remains bounded. [ABSTRACT FROM AUTHOR]

This paper describes the design and successful implementation of a constrained model predictive controller with integral action for the control of a Twin Rotor MIMO System (TRMS). The integral action guarantees zero steady-state error in set-point tracking with robustness toward perturbations of the nominal system parameters. In addition to saturation constraints on the input variables, hard constraints are imposed on the controlled output variables, i.e., on pitch and yaw angular positions, to avoid collisions with obstacles. The model predictive controller was designed using a high-fidelity nonlinear model of the TRMS developed in previous work. As an intermediate step, exact linearized models of the TRMS are obtained and their closed-form expressions are reported. The controller was tested experimentally, also showing its effectiveness in ensuring actual collision avoidance by the TRMS when physical obstacles were present. [ABSTRACT FROM AUTHOR]

In this paper, we propose a globally stable adaptive controller for the human shank motion tracking problem that appears in neuromuscular electrical stimulation systems. The control problem is complicated by the fact that the mathematical model of the human shank dynamics is nonlinear and the parameters enter in a nonlinear and nonseparable form. To solve the problem, we first derive a nonlinearly parameterized regressor equation (NLPRE) that is used with a new parameter estimator specifically tailored for this NLPRE. This estimator is then combined with a classical feedback linearizing controller to ensure the tracking objective is globally achieved. A further contribution of the paper is the proof that parameter convergence, and consequent global tracking, is guaranteed with an extremely weak interval excitation requirement. A simulation study comparing the proposed adaptive controller with existing ones in the literature shows comparable human shank tracking performance but with fewer parameter estimates and without requiring knowledge of bounds for the unknown parameters. [ABSTRACT FROM AUTHOR]

This paper examines the problem of simultaneously optimizing the spooling and cross-current flight trajectory of a tethered marine hydrokinetic kite using an analytic solution of its inverse dynamics. Tethered kites hold considerable promise for energy production, especially when undergoing cross-current motion. The novelty of this work lies in the use of an analytic solution of the inverse dynamics of the kite to solve the trajectory optimization problem. The term "inverse dynamics" refer to the process of obtaining an exact solution for the actuator inputs from the position, velocity, and acceleration of the kite. While the literature on tethered kites explores trajectory optimization in great detail, most of the work exploits the forward dynamics of the kite, and does not simultaneously optimize the spooling motion and cross-current trajectory. This paper formulates the co-optimization of the kite spooling and cross-current trajectory using a three degrees-of-freedom kite model, paired with an inelastic tether model. The analytic solution of the inverse dynamics is solved in terms of the roots of a fourth-order polynomial in terms of the angle of attack. A simulation study validates the optimization approach and shows that the kite is able to achieve significant energy production. [ABSTRACT FROM AUTHOR]

This paper presents a control-oriented model for describing the steady-state and dynamic behavior of a single-winged samara seed-pod in autorotative descent. A negligible lateral center of mass motion and constant, prescribed roll-angle to develop a simplified and compact model. Spanwise aerodynamic dependence is exchanged for an independent blade element representation with two tuned parameters to account for the effects of leading-edge vortex phenomena. The resulting model is a fourth-order nonlinear dynamical system. The accuracy of this model is established by validating it against our own experimental data as well as against those reported in the literature by other researchers. The validation exercise reveals that zero roll-angle is a viable assumption that significantly reduces model complexity while retaining accuracy. A necessary condition is derived for the existence of steady autorotation of the samara under free descent. Furthermore, a stability analysis is conducted suggesting that the eigenvalues of the fourth-order system, linearized about the autorotational equilibrium, can be well-represented by those of two decoupled two-dimensional systems. The analysis reveals the critical parameters that determine stability of sustained autorotation. Such stability analysis provides a platform for similar analytical exploration of future model improvements. The validity of this compact model suggests the plausibility of designing and controlling simple autorotative mechanisms based on these dynamics. [ABSTRACT FROM AUTHOR]

In this paper, we present combustor acoustics in a high-pressure liquid-fueled rich burn--quick quench--lean burn (RQL) styled swirl combustor with two separate fuel circuits. The fuel circuits are the primary (which has a pressure atomizer nozzle) and secondary (which has an air blast type nozzle) circuits. The data were acquired during two dynamical regimes--combustion noise, where there is an absence of large amplitude oscillations during the unsteady combustion process, and intermittency, where there are intermittent bursts of high amplitude oscillations that appear in a near-random fashion amidst regions of aperiodic low amplitude fluctuations. This dynamic transition from combustion noise to combustion intermittency is investigated experimentally by systematically varying the fuel equivalence ratio and primary-secondary fuel splits. Typical measures such as the amplitude of oscillations cannot serve as a measure of change in the dynamics from combustion noise to intermittency due to the highly turbulent nature. Hence, recurrence plots and complex networks are used to understand the differences in the combustor acoustics and velocity data during the two different regimes. We observe that the combustor transitions from stable operation to intermittency when the equivalence ratio is increased for a given primary fuel flowrate and conversely when the percentage of secondary fuel flowrate is increased for a given equivalence ratio. The contribution of this work is to demonstrate methodologies to detect combustion instability boundaries when approaching them from the stable side in highly turbulent, noisy combustors. [ABSTRACT FROM AUTHOR]

Thermoacoustic instabilities have plagued the operation of gas turbine engines for years and significant research is being conducted in detecting and understanding them. In this paper, an output only identification technique is employed for a noise induced dynamical system representing combustion instability behavior. This approach is called the output only observer Kalman filter identification (O³KID) and its first step solves for least squares from a set of algebraic equations constructed from just the measured output. The least squares solution gives the Markov parameters (impulse response) and the output residuals. The subsequent step takes the Markov parameters or the residuals to solve for the system matrices using any deterministic subspace identification method. In using this direct noniterative two-step algorithm, it is possible to estimate the eigenmodes and damping coefficients from output measured data. To validate the algorithm, a system of independent harmonic oscillators, excited by random noise is used to generate surrogate data representing pressure oscillations in a combustor prior to an instability. The error in estimating the eigen frequencies and damping are <1%. This fast direct approach could be used to provide an early warning indicator in industrial gas turbines by tracking the rate of damping of dominant eigenmodes. Additionally, saving the state space parameters periodically can serve as a data-lean option to track changes of the dynamics and across a gas turbine fleet. [ABSTRACT FROM AUTHOR]

Large eddy simulation is used to investigate the flashback mechanism caused by the combustion-induced vortex breakdown (CIVB) in a high-pressure lean-burn annular combustor with lean direct injection of kerosene. A single sector of the geometry, including a central pilot flame surrounded by a main flame, is simulated at takeoff conditions. A previously developed flamelet-based approach is used to model turbulence-combustion interactions due to its relatively low cost, allowing to simulate a sufficiently long time window. In stable operations, the flame stabilizes in an M-shape configuration and a periodic movement of the pilot jet, with the corresponding formation of a small recirculation bubble, is observed. Flashback is then observed, with the flame accelerating upstream toward the injector as already described in other studies. This large eddy simulation (LES), however, reveals a precursor partial blow-out of the main flame induced by a cluster of vortices appearing in the outer recirculation region. The combined effect of vortices and sudden quenching alters the mixing level close to the injector, causing first the main, then the pilot flame, to accelerate upstream, and initiate the CIVB cycle before the quenched region can re-ignite. Main and pilot flames partly extinguish as they cross their respective fuel injection point, and re-ignition follows due to the remnants of the reaction in the pilot stream. The process is investigated in detail, discussing the causes of CIVB-driven flashback in realistic lean-burn systems. [ABSTRACT FROM AUTHOR]

Industrial gas turbines commonly use lean premixed swirl stabilized combustors that are prone to thermo-acoustic instabilities. Combustor testing involves several steps ranging from atmospheric to high-pressure conditions. An open outlet boundary condition is maintained for atmospheric tests commonly, whereas high-pressure testing involves complex exit boundary conditions, which change the reflection coefficient and can affect the nature of instability. Current work aims at studying how the change in outlet boundary affects the nature of instability due to changes in the exit reflection coefficient and acoustic mode shape inside the combustor. A laboratory-scale industrial swirl burner that uses partially premixed methane and air at atmospheric conditions is analyzed for this purpose. A constant area contraction ratio of 6.5:1 is maintained at the exit of the combustor while varying the inlet Reynolds number at a constant global equivalence ratio. Flame dynamics based on conditional phase averaged OH* chemiluminescence images and spatial Rayleigh index maps were used to compare different flow rate and exit boundary cases. The outlet contraction affects both the frequency and amplitude of the dominant thermoacoustic mode. The orifice plate at the exit reduces the outlet reflection coefficient leading to a change in acoustic mode shape inside the combustor. Overall, the instability amplitude is reduced considerably for cases with an orifice plates at the exit boundary compared to open exit boundary cases. The results show the importance of defining outlet boundary conditions as a parameter in combustion instability studies. Care should be taken while comparing and interpreting results from different facilities where outlet boundary condition is different. [ABSTRACT FROM AUTHOR]

The formation of a ground vortex and its ingestion into an aero-engine intake under crosswind conditions play a significant role in the aerodynamic excitation of the fan. Using steady and unsteady numerical simulations, an analysis of the dynamics of several distortion features is presented. For a simplified intake at high crosswind velocities, there is a substantial movement of the ingested ground vortex at the aerodynamic interface plane (AIP). The ingested ground vortex follows a specific trajectory while varying both in size and strength. The transition from a periodic to an aperiodic regime of the intake distortion at the AIP occurs as the crosswind velocity is increased. Circumferential mode decomposition shows that the largest amplitude of the distortion occurs at the first circumferential mode, and the amplitudes of the higher modes decrease monotonically. Furthermore, the amplitude of the spatial harmonics is time-dependent, which may be an influential feature at the time of assessing fan forced response. [ABSTRACT FROM AUTHOR]

A microscopic vision is presented of a dual model of liquids (DML) starting from a solid picture. The task is accomplished first by showing how a series of experimental evidences and theoretical developments on liquid modeling, gathered for the first time, can be framed in a mesoscopic view of liquids, hypothesized as constituted by a population of dynamic aggregates of molecules, diving in an ocean of amorphous liquid. The pseudo-crystals interact with the rest of the liquid through harmonic elastic waves and anharmonic wave-packets propagating within and among the structures. The anharmonic interaction term is derived from "first principles"; it allows the exchange of energy and momentum between the wave packets and the molecule's clusters, determining the displacement of the latter within the medium, and the redistribution of the energy between external Degrees of Freedom (DoF) and internal collective degrees of the clusters. Among the novelties of this model is that it provides quantitative expressions of various extensive thermophysical properties. The introduction of the statistical number of excited DoF allows bypassing the problem of other dual models which are sometimes unable to correctly reproduce the expressions for those thermophysical quantities showing deviations due to the activation/de-activation of internal DoF. The interpretation of the relaxation times is given, their Order-of-Magnitude (OoM) calculated, and the way in which these times are involved in the different phases of the collective dynamics of liquids discussed. A comparison is provided with results obtained in the frame of Phonon theory of Liquid Thermodynamics, as well as the forecasts for the viscoelastic transition regions and with systems exhibiting k-gap. In the last part of the paper, theoretical insights and experiments are suggested as potential directions for future research and developments. [ABSTRACT FROM AUTHOR]

This paper solves the inverse dynamics of a tethered kite analytically. Specifically, the paper presents a procedure for determining the angle of attack, induced roll angle, and tether tension magnitude needed to achieve a desired combination of translational kite position, velocity, and acceleration. The focus of the paper is on energy harvesting kites. However, the underlying approach is applicable to other kite systems, such as kites for propulsion (e.g., SkySails, Hamburg, Germany). Solving inverse kite dynamics analytically is valuable for trajectory optimization, online state estimation, and the analysis of fundamental limitations on kite maneuvers. Previous work in the literature presents several models of kite dynamics, with varying degrees of fidelity and complexity. However, the nonlinearity of these models often makes them difficult to use for optimization, estimation, and control. The paper shows that, under reasonable assumptions, inverse kite dynamics can be solved in terms of the roots of a fourth-order polynomial function of angle of attack. This function has a geometric interpretation, providing insight into the multiplicity of resulting solutions. Moreover, for special cases including a kite with noncambered wings, these solutions can be computed analytically. A simulation validates the success of the proposed approach in computing inverse kite dynamics for a cross-current trajectory. [ABSTRACT FROM AUTHOR]

A safety-critical measure of legged locomotion performance is a robot's ability to track its desired time-varying position trajectory in an environment, which is herein termed as "global-position tracking." This paper introduces a nonlinear control approach that achieves asymptotic global-position tracking for three-dimensional (3D) bipedal robots. Designing a global-position tracking controller presents a challenging problem due to the complex hybrid robot model and the time-varying desired global-position trajectory. Toward tackling this problem, the first main contribution is the construction of impact invariance to ensure all desired trajectories respect the foot-landing impact dynamics, which is a necessary condition for realizing asymptotic tracking of hybrid walking systems. Thanks to their independence of the desired global position, these conditions can be exploited to decouple the higher-level planning of the global position and the lower-level planning of the remaining trajectories, thereby greatly alleviating the computational burden of motion planning. The second main contribution is the Lyapunov-based stability analysis of the hybrid closed-loop system, which produces sufficient conditions to guide the controller design for achieving asymptotic global-position tracking during fully actuated walking. Simulations and experiments on a 3D bipedal robot with twenty revolute joints confirm the validity of the proposed control approach in guaranteeing accurate tracking. [ABSTRACT FROM AUTHOR]

This paper proposes an automatic time-energy efficient robust control (ATERC) deployment approach for selecting either a near-optimal closed-loop control law or a robust control law based on the requirement of the system. The near-optimal closed-loop control law is designed by applying the population-based sine-cosine algorithm (SCA) to the considered interceptor problem. While the robust control law is formulated by using an artificial time delayed control (TDC) approach. In presence of external disturbances, the ATERC methodology deploys the TDC-based robust guidance law to the interceptor, while in the absence of such uncertainties the SCA-based near-optimal guidance law is applied in order to improve the time-energy minimization. This guidance approach also incorporates input saturation which expands its applicability. Using Lyapunov stability analysis, this work establishes an uniformly ultimately bounded (UUB) stability for the discussed system on application of the proposed control approach. Extensive simulation studies involving nonmaneuvering targets and targets performing bank-to-bank maneuver, affirms the efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

Accessing difficult to reach hydrocarbon reservoirs while simultaneously reducing risk and increasing efficiency demonstrates a need for improved autonomous directional control of rotary steerable systems (RSS). The inherently uncertain drilling environment presents a challenge for control algorithms and human operators alike, where model mismatch can be significant and the parameters are time varying. Parameter estimation can improve the performance of steering controllers through model adaptation as well as provide valuable information to human operators. This paper proposes the use of a Markov Chain Monte Carlo (MCMC) method to estimate time-varying model parameters in real-time using only measurements commonly obtained while drilling. The proposed method is evaluated on historical field data and its accuracy is quantified by prediction accuracy to achieve a mean absolute error of 0.68 deg over 30 m. Next, the proposed method is used to adapt the model of a model predictive controller (MPC) and its performance is compared with a static MPC in closed-loop simulation of a prototypical drilling scenario. The estimator reduces tracking error of the MPC by 93.36% and produces a higher quality borehole. Finally, the utility of estimation for human-in-the-loop operation is explored through the design of an early warning system (EWS). The posterior distribution produced by MCMC is utilized in the EWS to predict the probability of undesirable future trajectories. By providing automatic alerts, the EWS serves as a safety mechanism that enhances operators' proficiency when monitoring several autonomously drilled wells. [ABSTRACT FROM AUTHOR]

Driver's steering torque is an essential signal for automated and assistance driving systems to interpret the human driver's intention. In a steer-by-wire (SBW) apparatus, due to the inevitable couplings between the driver steering, electrical motor, and viscous frictional torques, such a vital signal cannot be directly measured via a torque transducer. Instead, model-based estimators are considered a more practicable route. Toward this end, this paper introduces a novel mixed L1/H2 observer to achieve a robust estimation respecting the human driver's steering torque in human-alone and human-automation shared driving. On the one hand, the L1 induced norm from the process disturbance to the estimation error is attenuated. On the other hand, the H2 synthesis seeks to suppress the effects of measurement noises from the steering angle encoder and the motor's current sensor. Driving simulator human subject experiments are effectuated to justify the proposed strategy and manifest its superiorities over a benchmark method. [ABSTRACT FROM AUTHOR]

Roll-to-roll (R2R) dry transfer is an important process for manufacturing of large-scale two-dimensional (2D) materials and printed flexible electronics. Existing research has demonstrated the feasibility of dry transfer of 2D materials in a roll-to-roll setting with mechanical peeling. However, the process presents a significant challenge to system control due to the lack of understanding of the mechanical peeling behavior and the complexity of the nonlinear system dynamics. In this study, an R2R peeling process model is developed to understand the dynamic interaction among the peeling process parameters, including adhesion energy, peeling force, angle, and speed. Both simulation and experimental studies are conducted to validate the model. It is shown that the dynamic system model can capture the transient behavior of the R2R mechanical peeling process and be used for the process analysis and control design. [ABSTRACT FROM AUTHOR]

In previous work, a driver model with visual and vestibular sensory dynamics was developed, identified, and validated, using data from moving-base driving simulator experiments. In this paper, the predictions, applications, and limitations of the driver model are explored through a series of simulations. The aim is to address as yet unanswered questions about the role of visual and vestibular sensory dynamics in the driver-vehicle system. The visual system is found to be the dominant sensory system, with the influence of vestibular measurements increasing with the proportion of random disturbances on the vehicle. State perception errors increase significantly with the proportion of random disturbances on the vehicle. The driver's simulated control performance is unchanged with signal amplitude above perception threshold levels, although it is slightly affected by high-pass filtering of the physical motion such as might be experienced in a driving simulator. The sensory driver model led to a significantly different optimum value of vehicle center of mass position compared to that obtained using an idealized driver model. The results motivate the adoption of sensory driver models in a vehicle design setting. Further work could be undertaken to improve the sensorimotor noise model. [ABSTRACT FROM AUTHOR]

Articulating landing gear that use closed-loop feedback control are proven to expand the landing capabilities of rotorcraft on sloped and rough terrain. These systems are commonly referred to as robotic landing gear (RLG). Modern RLG systems have limitations for landing on dynamic platforms because their controllers do not incorporate fuselage roll and roll rate feedback. This work presents a proven crashworthy cable-driven RLG system for the commercial S-100 Camcopter that expands static landing zone limits by a factor of three and enables dynamic platform landings in rough sea state (SS) conditions. A new roll and foot-force feedback fused control algorithm is developed to enable ship deck landings of an RLG equipped S-100 without the need for deck lock or advanced vision-based landing systems. Multibody dynamic simulations of the aircraft, landing gear, and new control system show the benefits of this combined roll and force feedback approach. Results include experimental dynamic landings on platforms rolling under sinusoidal motion and simulated SS conditions. The experiments demonstrate, in a limited fashion, the usability of the RLG through ground experimentation, and the results are compared to simulations. Additional simulations of landings of the S-100 with rigid and active landing gear with more challenging landing conditions than experimentally tested are presented. Such results aid in understanding how RLG with this new roll and contact force fused controller prevent dynamic rollover. [ABSTRACT FROM AUTHOR]

This article analyzes the combined parameter and state identifiability for a model of a cancerous tumor's growth dynamics. The model describes the impact of drug administration on the growth of two populations of cancer cells: a drug-sensitive population and a drug-resistant population. The model's dynamic behavior depends on the underlying values of its state variables and parameters, including the initial sizes and growth rates of the drug-sensitive and drug-resistant populations, respectively. The article's primary goal is to use Fisher identifiability analysis to derive and analyze the Cramér-Rao theoretical bounds on the best-achievable accuracy with which this estimation can be performed locally. This extends previous work by the authors, which focused solely on state estimation accuracy. This analysis highlights two key scenarios where estimation accuracy is particularly poor. First, a critical drug administration rate exists where the model's state observability is lost, thereby making the independent estimation of the drug-sensitive and drug-resistant population sizes impossible. Second, a different critical drug administration rate exists that brings the overall growth rate of the drug-sensitive population to zero, thereby worsening model parameter identifiability. [ABSTRACT FROM AUTHOR]

There is growing interest in the use of the filtered basis functions (FBF) approach to track linear systems, especially nonminimum phase (NMP) plants, because of its distinct advantages compared to other tracking control methods in the literature. The FBF approach expresses the control input to the plant as a linear combination of basis functions with unknown coefficients. The basis functions are forward filtered through the plant dynamics, and the coefficients are selected such that tracking error is minimized. Similar to other feedforward control methods, the tracking accuracy of the FBF approach deteriorates in the presence of uncertainties. However, unlike other methods, the FBF approach presents flexibility in terms of the choice of the basis functions, which can be used to improve its accuracy. This paper analyzes the effect of the choice of the basis functions on the tracking accuracy of FBF, in the presence of uncertainties, using the Frobenius norm of the lifted system representation (LSR) of FBF's error dynamics. Based on the analysis, a methodology for optimal selection of basis functions to maximize robustness is proposed, together with an approach to avoid large control effort when it is applied to NMP systems. The basis functions resulting from this process are called robust basis functions. Applied experimentally to a desktop three-dimensional (3D) printer with uncertain NMP dynamics, up to 48% improvement in tracking accuracy is achieved using the proposed robust basis functions compared to B-splines, while utilizing much less control effort. [ABSTRACT FROM AUTHOR]

A complex motion encountered in a number of robotic, industrial, and defense applications is the motion of a rigid body when one of its body-fixed axes tracks a desired pointing direction while it rotates at high angular velocity around the pointing direction (PDAV); during this motion, high frequency precession/nutation oscillations arise. This work analyzes the global/local closed-loop (CL) behavior induced by a developed geometric, PDAV controller and studies the high frequency precession/nutation oscillations that characterize PDAV motions. This is done via geometrically exact linearization and via simulation techniques that amount to charting the smooth CL vector fields on the manifold. A method to quickly estimate the frequency of the precession/nutation oscillations is developed and can be used for sizing actuators. A thorough understanding of the behavior of the CL flow induced by the PDAV controller is achieved, allowing the control engineer to anticipate/have a rough estimate of the system CL response. [ABSTRACT FROM AUTHOR]

In this paper, we study the analytical and experimental control of a seven degrees-of-freedom (7DOF) robot manipulator. A model-free decentralized adaptive control strategy is presented for the tracking control of the manipulator. The problem formulation and experimental results demonstrate the computational efficiency and simplicity of the proposed method. The results presented here are one of the first known experiments on a redundant 7DOF robot. The efficacy of the adaptive decentralized controller is demonstrated experimentally by using the Baxter robot to track a desired trajectory. Simulation and experimental results clearly demonstrate the versatility, tracking performance, and computational efficiency of this method. [ABSTRACT FROM AUTHOR]

The primary goal of this paper is to develop a formal foundation to design nonlinear feedback control algorithms that intrinsically couple legged robots with bio-inspired tails for robust locomotion in the presence of external disturbances. We present a hierarchical control scheme in which a high-level and real-time path planner, based on an event-based model predictive control (MPC), computes the optimal motion of the center of mass (COM) and tail trajectories. The MPC framework is developed for an innovative reduced-order linear inverted pendulum (LIP) model that is augmented with the tail dynamics. At the lower level of the control scheme, a nonlinear controller is implemented through the use of quadratic programming (QP) and virtual constraints to force the full-order dynamical model to track the prescribed optimal trajectories of the COM and tail while maintaining feasible ground reaction forces at the leg ends. The potential of the analytical results is numerically verified on a full-order simulation model of a quadrupedal robot augmented with a tail with a total of 20 degrees-of-freedom. The numerical studies demonstrate that the proposed control scheme coupled with the tail dynamics can significantly reduce the effect of external disturbances during quadrupedal locomotion. [ABSTRACT FROM AUTHOR]

The use of lean, premixed fuel and air mixtures is a common strategy to reduce NOx emissions in gas turbine combustors. However, this strategy causes an increased susceptibility to self-excited instability, which manifests as fluctuations in heat release rate, flow velocity, and combustor acoustics that oscillate in-phase in a feedback loop. This study considers the effect of the level of premixedness on the self-excited instability in a single-nozzle combustor. In this system, the fuel can be injected inside the nozzle to create a partially-premixed mixture or far upstream to create a fully-premixed mixture, varying the level of premixedness of the fuel and air entering the combustor. When global equivalence ratio is held constant, the cases with higher levels of premixing have higher instability amplitudes. High-speed CH* chemiluminescence imaging shows that the flame for these cases is more compact and the distribution of the heat release rate oscillations is more concentrated near the corner of the combustor in the outer recirculation zones. Rayleigh index images, which are a metric for the relative phase of pressure and heat release rate oscillations, suggest that vortex rollup in the corner region is primarily responsible for determining instability characteristics when premixedness is varied. This finding is further supported through analysis of local flame edge dynamics. [ABSTRACT FROM AUTHOR]

Particle image velocimetry is used to experimentally study the wake dynamics behind a near-wall square cylinder subjected to a thick oncoming turbulent boundary layer. The turbulent boundary layer thickness was 3.6 times the cylinder height (h) while the Reynolds number based on the freestream velocity and the cylinder height was 12,750. The gap distance (G) between the bottom face of the cylinder and the wall was varied, resulting in gap ratios (G/h) of 0, 0.3, 0.5, 1.0, 2.0, 4.0, and 8.0. The effects of varying the gap ratio on the mean flow, Reynolds stresses, triple velocity correlation, two-point autocorrelation, and the unsteady wake characteristics were examined. The results indicate that as gap ratio decreases, asymmetry in the wake flow becomes more pronounced, and the size of the mean separation bubbles increases. The magnitudes of the Reynolds stresses and triple velocity correlations generally decrease with the decreasing gap ratio. Moreover, the size of the large-scale structures increases with decreasing gap ratio, and the critical gap ratio, below which Kármán vortex shedding is suppressed, is found to be 0.3. The dominant Strouhal number in the wake flow expressed in terms of the streamwise mean velocity at the cylinder vertical midpoint increases as gap ratio decreases while that based on the freestream velocity is less sensitive to gap ratio for the offset cases (G/h> 0). [ABSTRACT FROM AUTHOR]

Among all aquatic species, mantas and rays swim by flapping their pectoral fins; this motion is similar to other fishes in terms of efficiency, but it gives better maneuverability and agility in turning. The fin's motion is featured by a traveling wave going opposite to the forward motion, producing a force thanks to momentum conservation. This article aims at understanding the swimming dynamics of rays, focusing on energy efficiency. A computational fluid dynamics (CFD) model of the swimming motion of a cownose ray has been implemented in openfoam, simulating the acceleration of the fish from still to the steady-state velocity using an overset mesh. In this analysis, the one degree-of-freedom dynamics of forward swimming is solved together with the fluid velocity and pressure. The effect of frequency and wavelength of fin motion on thrust, power, and velocity has been investigated and an analysis of the vortices in the wake showed has been performed. The energy efficiency of a self-propelled body has been defined in a novel way and it has been calculated for different motion conditions. The results showed that batoid fishes swim with high energy efficiency and that they are a promising source of inspiration for biomimetic autonomous underwater vehicles. [ABSTRACT FROM AUTHOR]

Through chemostat reactors, organisms can be observed under laboratory conditions. Hereby, the reactor contains the biomass, whose growth can be controlled via the dilution rate, respectively, the speed of a pump. Due to physical limitations, input constraints need to be considered. The population density in the reactor can be described by a hyperbolic nonlinear integro partial differential equation (IPDE) of first order. The steady-states and generalized eigenvalues and eigenmodes of these IPDE are determined. In order to track a desired reference trajectory, an optimal and an inversion-based feedforward control are designed. For the optimal feedforward control, the singular arc of the control is calculated and a switching strategy is stated, which explicitly considers the input constraints. For the inversion-based feedforward control, the IPDE is first linearized around the steady-state. To comply with the input constraints, a control system simulator is designed. For the simulation model, the IPDE is approximated using Galerkin's method. Simulations show the functionality of the designed controls and provide the basis for comparison. The inversion-based feedforward control operates well near the steady-state, whereas the performance of the optimal feedforward control is not bounded to the proximity to the steady-state. [ABSTRACT FROM AUTHOR]

Lithium iron phosphate (LiFePO4 or LFP) is a common active material in lithium-ion batteries. It has been observed that this material undergoes phase transitions during the normal charge and discharge operation of the battery. Electrochemical models of lithium-ion batteries can be modified to account for this phenomenon at the expense of some added complexity. We explore this problem for the single particle model (SPM) where the underlying dynamic model for diffusion of lithium ions in phase transition materials is a partial differential equation (PDE) with a moving boundary. We derive a novel boundary observer to estimate the concentration of lithium ions together with a moving boundary radius from the SPM via the backstepping method for PDEs, and simulations are provided to illustrate the performance of the observer. Our comments are stated on the gap between the proposed observer and a complete state-of-charge (SoC) estimation algorithm for lithium-ion batteries with phase transition materials. [ABSTRACT FROM AUTHOR]

This paper addresses the compensation of wave actuator dynamics in scalar extremum seeking (ES) for static maps. Infinite-dimensional systems described by partial differential equations (PDEs) of wave type have not been considered so far in the literature of ES. A distributed-parameter-based control law using back-stepping approach and Neumann actuation is initially proposed. Local exponential stability as well as practical convergence to an arbitrarily small neighborhood of the unknown extremum point is guaranteed by employing Lyapunov-Krasovskii functionals and averaging theory in infinite dimensions. Thereafter, the extension for wave equations with Dirichlet actuation, antistable wave PDEs as well as the design for the delay-wave PDE cascade are also discussed. Numerical simulations illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

This paper first characterizes the acoustic field of two annular combustors by means of data from acoustic pressure sensors. In particular, the amplitude, orientation, and nature of the acoustic field of azimuthal order n are characterized. The dependence of the pulsation amplitude on the azimuthal location in the chamber is discussed, and a protection scheme making use of just one sensor is proposed. The governing equations are then introduced, and a low-order model of the instabilities is discussed. The model accounts for the nonlinear response of M distinct flames, for system acoustic losses by means of an acoustic damping coefficient α and for the turbulent combustion noise, modeled by means of the background noise coefficient σ. Keeping the response of the flames arbitrary and in principle different from flame to flame, we show that, together with α and σ, only the sum of their responses and their 2n Fourier component in the azimuthal direction affect the dynamics of the azimuthal instability. The existing result that only this 2n Fourier component affects the stability of standing limit-cycle solutions is recovered. It is found that this result applies also to the case of a nonhomogeneous flame response in the annulus, and to flame responses that respond to the azimuthal acoustic velocity. Finally, a parametric flame model is proposed, depending on a linear driving gain β and a nonlinear saturation constant κ. The model is first mapped from continuous time to discrete time, and then recast as a probabilistic Markovian model. The identification of the parameters {α,β,κ,σ} is then carried out on engine time-series data. The optimal four parameters {α,σ,β,κ} are estimated as the values that maximize the data likelihood. Once the parameters have been estimated, the phase space of the identified low-order problem is discussed on selected invariant manifolds of the dynamical system. [ABSTRACT FROM AUTHOR]

This paper develops boundary control for freeway traffic with a downstream bottleneck. Traffic on a freeway segment with capacity drop at outlet of the segment is a common phenomenon that leads to traffic bottleneck problem. The capacity drop can be caused by lane-drop, hills, tunnel, bridge, or curvature on the road. If incoming traffic flow remains unchanged, traffic congestion forms upstream of the bottleneck since the upstream traffic demand exceeds its capacity. Therefore, it is important to regulate the incoming traffic flow of the segment to avoid overloading the bottleneck area. Traffic densities on the freeway segment are described with the Lighthill-Whitham-Richards (LWR) macroscopic partial differential equation (PDE) model. The incoming flow at the inlet of the freeway segment is controlled so that the optimal density that maximizes the outgoing flow is reached and the traffic congestion upstream of the bottleneck is mitigated. The density and traffic flow relation at the bottleneck area, usually described with fundamental diagram, is considered to be unknown. We tackle this problem using extremum seeking (ES) control with delay compensation for the LWR PDE. ES control, a nonmodel-based approach for real-time optimization, is adopted to find the optimal density for the unknown fundamental diagram. A predictor feedback control design is proposed to compensate the delay effect of traffic dynamics in the freeway segment. In the end, simulation results are obtained to validate a desired performance of the controller on the nonlinear LWR model with an unknown fundamental diagram. [ABSTRACT FROM AUTHOR]

We present a reduced-order model (ROM) for the temperature and oxygen storage dynamics of three way catalysts (TWCs). The thermal and oxygen storage dynamics are described using a set of coupled, nonlinear partial differential equations (PDEs) developed and experimentally validated in previous research. Advancements in on-board diagnostic (OBD) design are moving in the direction of using physics-based models that would retain as much physical insights as possible. Retaining the one-dimensional (1D) evolution of the internal storage dynamics along the device length is key for the development of accurate emission control strategies. In this work, we adopt the numerical projection orthogonal approach combined with the analytical features of Galerkin reduction method to define a set of ordinary differential equations (ODEs) to describe the oxygen storage and temperature dynamics throughout the device life. Using experimental data collected over three TWC devices, each of different age, and under the excitation of different real drive cycles, we validate the model and quantify the relation between the number of reduced-order states versus model accuracy for devices both new and at different stages of life. The input dependent characteristics of the developed reduced-model model is also investigated using a power spectral density (PSD) analysis. Finally, we show that an initial tuning of the reduced model parameters for a fresh catalyst guarantees satisfactory modeling performance throughout the device life, regardless of the driving scenario. [ABSTRACT FROM AUTHOR]

This paper extends the recently developed quasi-spectral model predictive static programming (QS-MPSP) to include state and control path-constraints and yet retain its computational efficiency. This is achieved by (i) formulating the entire problem in the control variables alone by (a) converting the system dynamics to an equivalent algebraic constraint and (b) converting the state constraints to equivalent control constraints, both of which is done by manipulating the system dynamics, (ii) representing the control variables in Quasi-spectral form, which makes the number of free-variables independent of time-grids and (iii) using a computationally efficient optimization algorithm to solve this low-dimensional problem. This generic computationally efficient technique is utilized next as an effective lead angle, and lateral acceleration constrained optimal missile guidance to intercept incoming high-speed ballistic targets with high precision successfully. Both of these constraints, as well as near-zero miss-distance, are of high practical significance for this challenging problem. Extensive three-dimensional simulation studies show the effectiveness of the newly proposed constrained QS-MPSP guidance algorithm. Six degrees-of-freedom simulation studies have also been carried out using autopilot in the loop to validate the results more realistically. [ABSTRACT FROM AUTHOR]

Conventional physics-based or experimental-based approaches for gas turbine combustion tuning are time consuming and cost intensive. Recent advances in data analytics provide an alternative method. In this paper, we present a cross-disciplinary study on the combustion tuning of an F-class gas turbine that combines machine learning with physics understanding. An artificial-neural-network-based (ANN) model is developed to predict the combustion performance (outputs), including NOx emissions, combustion dynamics, combustor vibrational acceleration, and turbine exhaust temperature. The inputs of the ANN model are identified by analyzing the key operating variables that impact the combustion performance, such as the pilot and the premixed fuel flow, and the inlet guide vane angle. The ANN model is trained by field data from an F-class gas turbine power plant. The trained model is able to describe the combustion performance at an acceptable accuracy in a wide range of operating conditions. In combination with the genetic algorithm, the model is applied to optimize the combustion performance of the gas turbine. Results demonstrate that the data-driven method offers a promising alternative for combustion tuning at a low cost and fast turn-around. [ABSTRACT FROM AUTHOR]

This paper presents experimental and numerical investigation of mistuned forced responses of an integrally bladed disk with full set of underplatform dampers (UPDs). This research aims at providing: 1. An experimental benchmark for nonlinear dynamics of a mistuned bladed disks with UPDs. 2. A numerical model that can account for features of a mistuned forced response level. Accordingly, a detailed experimental campaign is conducted on a static test rig called Octopus. This rig is specifically designed to investigate the dynamics of a full-scale integrally bladed disk (blisk) with UPDs in a noncontact manner so that the dynamic response of the system is not modified. The effect of mistuning on experimental forced response levels is assessed and a linearized model is proposed to predict the modulation of frequency response functions (FRFs) due to the frequency splitting. In the development of the model, the mistuning pattern identified from the linear blisk without UPDs is used and it is assumed that adding the dampers does not change the structural mistuning of the blisk. In this study, the fundamental mistuning model identification (FMM ID) was employed to identify the mistuning pattern of the blisk. It is shown that the proposed model successfully predicts the modulation of linear mistuned FRFs. The linearized model is also able to predict the modulation of nonlinear mistuned FRFs in stick condition (when nonlinear friction damping is negligible) with a good accuracy validating this assumption that adding the dampers does not change the mistuning pattern. [ABSTRACT FROM AUTHOR]

This study focuses on the measured changes in dynamic behavior exhibited by eight synthetic vocal fold models with varying mechanical properties. Uniaxial tensile testing was conducted to determine changes in mechanical properties between materials made from silicone rubber and polydimethylsiloxane with varying mixing ratios. The results of the mechanical testing showed that the elastic modulus, E, varied from 20.6 to 437.4 kPa, the measured Poisson ratios, ν, spanned the range of 0.43-0.48, and the density, ρVF⁠, varied from 0.86 to 1.02 g/cm³ across the eight samples. Vocal fold models were dynamically tested using a custom-built experimental setup that supplied a heated and humidified airflow to the synthetic vocal folds. The resulting sounds were recorded and analyzed to identify the change in fundamental frequency which spanned 66.8 to 342.6 Hz across the eight samples. In addition, a mathematical aeroelastic model of phonation was implemented to further investigate the relationship between the mechanical properties and phonation frequency. Finally, a proof-of-concept magnetic actuation method was demonstrated using magnetic elastomers to deform the synthetic vocal folds through the use of an electromagnet. [ABSTRACT FROM AUTHOR]

This paper studies the bipartite consensus problem of a swarm of robots whose dynamics are formulated by Lagrangian equations. Two distributed bipartite consensus control protocols are proposed for a swarm of robots without a leader or with a virtual leader. For the nonleader case, the networked Lagrangian system can reach static bipartite consensus under the control protocol developed, and the final convergent states can be explicitly determined by the specific structure of the Laplacian matrix associated with the cooperative-competitive network topology. For the virtual leader case, all the followers can track the leader's state in a bipartite formation to realize bipartite tracking consensus. Finally, the simulation results are given to verify the theoretical results. [ABSTRACT FROM AUTHOR]