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The primary goal of this paper is to develop a formal foundation to design an adaptive output feedback predictor for a class of unknown systems where parameters and order are unknown or high-dimensional. We present a reduced-order adaptive output-predictor scheme based on modal reduction and Lyapunov's method. Moreover, the credibility of the proposed reduced-order adaptive output-predictor scheme is validated by mathematical proof and numerical studies. [ABSTRACT FROM AUTHOR]

This paper presents a modular approach to motion planning with provable stability guarantees for robots that move through changing environments via periodic locomotion behaviors. We focus on dynamic walkers as a paradigm for such systems, although the tools developed in this paper can be used to support general compositional approaches to robot motion planning with dynamic movement primitives (DMPs). By formulating the planning process as a switching system with multiple equilibria (SSME), we prove that the system's evolution remains within explicitly characterized trapping regions in the state space under suitable constraints on the frequency of switching among the DMPs. These conditions encapsulate the low-level stability limitations in a form that can be easily communicated to the planner. Furthermore, we show how the available primitives can be safely composed online in a receding horizon manner to enable the robot to react to moving obstacles. The proposed framework can be applied in a wide class of 3D bipedal walking models, and offers a modular approach for integrating readily available low-level locomotion control and high-level planning methods. [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]

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]

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]