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At least 577 records · Page 32

Optimization for efficient structure-control systems

The efficiency of a structure-control system is a nondimensional parameter which indicates the fraction of the total control power expended usefully in controlling a finite-dimensional system. The balance of control power is wasted on the truncated dynamics serving no useful purpose towards the control objectives. Recently, it has been demonstrated that the concept of efficiency can be used to address a number of control issues encountered in the control of dynamic systems such as the spillover effects, selection of a good input configuration and obtaining reduced order control models. Reference (1) introduced the concept and presented analyses of several Linear Quadratic Regulator designs on the basis of their efficiencies. Encouraged by the results of Ref. (1), Ref. (2) introduces an efficiency modal analysis of a structure-control system which gives an internal characterization of the controller design and establishes the link between the control design and the initial disturbances to affect efficient structure-control system designs. The efficiency modal analysis leads to identification of principal controller directions (or controller modes) distinct from the structural natural modes. Thus ultimately, many issues of the structure-control system revolve around the idea of insuring compatibility of the structural modes and the controller modes with each other, the better the match the higher the efficiency. A key feature in controlling a reduced order model of a high dimensional (or infinity-dimensional distributed parameter system) structural dynamic system must be to achieve high efficiency of the control system while satisfying the control objectives and/or constraints. Formally, this can be achieved by designing the control system and structural parameters simultaneously within an optimization framework. The subject of this paper is to present such a design procedure.

Oz, Hayrani↗

Phase change energy storage for solar dynamic power systems

This paper presents the results of a transient computer simulation that was developed to study phase change energy storage techniques for Space Station Freedom (SSF) solar dynamic (SD) power systems. Such SD systems may be used in future growth SSF configurations. Two solar dynamic options are considered in this paper: Brayton and Rankine. Model elements consist of a single node receiver and concentrator, and takes into account overall heat engine efficiency and power distribution characteristics. The simulation not only computes the energy stored in the receiver phase change material (PCM), but also the amount of the PCM required for various combinations of load demands and power system mission constraints. For a solar dynamic power system in low earth orbit, the amount of stored PCM energy is calculated by balancing the solar energy input and the energy consumed by the loads corrected by an overall system efficiency. The model assumes an average 75 kW SD power system load profile which is connected to user loads via dedicated power distribution channels. The model then calculates the stored energy in the receiver and subsequently estimates the quantity of PCM necessary to meet peaking and contingency requirements. The model can also be used to conduct trade studies on the performance of SD power systems using different storage materials.

Chiaramonte, F. P.↗

Integrated system identification and modal state estimation for control of flexible space structures

A novel approach of integrated system identification and modal state estimation is proposed for control of linear dynamical systems including flexible space structures. There are four steps involved in this approach. First, the relation between a stochastic state space model of a dynamical system and the coefficients of its autoregressive model with exogenous input is derived. Second, an adaptive least-squares transversal predictor is used to estimate the coefficients of the model. Third, a state space model and a steady state Kalman filter gain of the dynamical system are then identified from the coefficients of the model by using the eigensystem realization algorithm. Fourth, a modal state estimator is constructed using the modal parameters of the identified model. On-line implementation of this algorithm can continually improve the modal parameters and the filter gain. It can also gradually update the system model when the system characteristics are slowly changing. A numerical example is used to illustrate the feasibility of the new approach.

Chen, Chung-Wen↗

Experimental considerations and applications for time-resolved impedance on silicon-anode battery systems

Dynamic electrochemical impedance spectroscopy (dEIS) utilizes a superimposed multi-sinusoidal waveform and enables temporally resolved investigations on various electrochemical processes; however, the signal-to-noise ratio must be maximized while retaining linearity and stationarity within the system. In the present work, we probe the impact of the waveform’s total amplitude as well as the waveform and phase profiles. The equal amplitude multi-sinusoidal waveform with 35 mV total amplitude (<1 mV per frequency) and random phase profile exhibits the lowest impedance noise. This input signal is sufficient in avoiding the high frequency signal attenuation from the potentiostat’s low-pass filter. Additionally, we demonstrate the optimized dEIS waveform’s utility in investigating surface passivation within thin-film and composite silicon (Si) anodes. Within a two-electrode Si-lithium metal coin cell, the charge transfer resistance (RCT) associated with alloying kinetics dominates the overall impedance. RCT increases with state of charge indicating a kinetic bottleneck at higher lithiation states. To explore this further, we utilize a three-electrode Si-LiNi0.8Mn0.1Co0.1O2 pouch cell to deconvolute the Si impedance contributions. The evolution of the solid electrolyte interphase (SEI) and charge transfer resistances correlate to specific Li–Si alloy phases. We attribute this to the influence of Si particle volume expansion on SEI instabilities and a kinetic bottleneck at higher lithiation states.

Lam, Steven [ORNL]↗

Neural networks for self-learning control systems

It is shown how a neural network can learn of its own accord to control a nonlinear dynamic system. An emulator, a multilayered neural network, learns to identify the system's dynamic characteristics. The controller, another multilayered neural network, next learns to control the emulator. The self-trained controller is then used to control the actual dynamic system. The learning process continues as the emulator and controller improve and track the physical process. An example is given to illustrate these ideas. The 'truck backer-upper,' a neural network controller that steers a trailer truck while the truck is backing up to a loading dock, is demonstrated. The controller is able to guide the truck to the dock from almost any initial position. The technique explored should be applicable to a wide variety of nonlinear control problems.

Nguyen, Derrick H.↗

Memory-efficient nonsmooth dynamic optimization using adaptive randomized compression

Dynamic optimization problems arise in many applications including flow control, full waveform inversion, and medical imaging. These problems are plagued by significant computational challenges. One such challenge — and the focus of this work — is the memory limitation induced by the size of the underlying dynamical system. In particular, the entire dynamic trajectory is required for derivative computation and therefore must be stored or recomputed using, e.g., checkpointing. Although recent work demonstrated the use of adaptive randomized sketching to overcome the memory challenge, that work only applies to smooth unconstrained problems, prohibiting its use for nonsmooth regularized and constrained problems. The inclusion of nonsmooth regularizers and constraints is critical as they often arise in an attempt to preserve certain physical properties or to promote sparsity. To solve these problems, we introduce a trust-region algorithm for minimizing the sum of a smooth nonconvex function and a nonsmooth convex function that leverages randomized sketching to compress the dynamical system trajectories and adaptively adjust the sketch rank to satisfy a gradient inexactness condition. We prove convergence of this algorithm and demonstrate that it achieves substantial memory reduction on three discretized PDE-constrained optimization applications.

97 MATHEMATICS AND COMPUTING↗

Systems and Methods for Derivative-Free Adaptive Control

An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.

Yucelen, Tansel↗

Thermal energy storage for a space solar dynamic power system

In the past, NASA has employed solar photovoltaic devices for long-duration missions. Thus, the Skylab system has operated with a silicon photovoltaic array and a nickel-cadmium electrochemical system energy storage system. Difficulties regarding the employment of such a system for the larger power requirements of the Space Station are related to a low orbit system efficiency and the large weight of the battery. For this reason the employment of a solar dynamic power system (SDPS) has been considered. The primary components of an SDPS include a concentrating mirror, a heat receiver, a thermal energy storage (TES) system, a thermodynamic heat engine, an alternator, and a heat rejection system. The heat-engine types under consideration are a Brayton cycle engine, an organic Rankine cycle engine, and a free-piston/linear-alternator Stirling cycle engine. Attention is given to a system description, TES integration concepts, and a TES technology assessment.

Faget, N. M.↗

Numerical Modeling of No Vent Filling of a Cryogenic Tank with Thermo-dynamic Vent System Assisted Injector

This paper presents a multi-node finite volume model of No Vent Filling (NVF) of a cryogenic tank with Thermo-dynamic Vent System (TVS) assisted injector, using the Generalized Fluid System Simulation Program (GFSSP), a general purpose flow network code. NVF tests were conducted in a CRYOgenic Orbital Testbed (CRYOTE) tank which was filled by liquid nitrogen using a TVS assisted injector with vent valve closed during the entire filling process. In TVS assisted injector, the liquid flow splits into two streams: one stream is routed to a Joule-Thomson (J-T) orifice where the flow immediately flashes from liquid to vapor or two phase mixture because the downstream to J-T leg is maintained at vacuum level.; the other stream is injected into the tank after being cooled by cold vapor of J-T leg in a heat exchanger. The flow through J-T leg is also used to cool the outer metal matrix of the injector which in turn cools the vapor in the tank ullage. The cooling of vapor in the ullage by cold injector surface reduces ullage pressure that allows liquid to enter and fill the tank. An integrated numerical model of the test set up was developed. The model included the dual lines of TVS assisted injector, tank and tank wall. The tank was discretized into multiple fluid nodes and branches to represent the ullage and liquid nitrogen and multiple solid nodes to represent the tank wall and structure. The heat transfer between solid to fluid was calculated from pool boiling correlations which include film, transition, and nucleate boiling, as well as natural convection during pre- and post-boiling. The model also accounts for the condensation of vapor at ullage-injector interface and when it comes in contact with the liquid spray. The predicted pressure, resident mass, wall temperature in the tank were compared with the test data.

Alok Majumdar↗

Session 6: Dynamic Modeling and Systems Analysis

These presentations cover some of the ongoing work in dynamic modeling and dynamic systems analysis. The first presentation discusses dynamic systems analysis and how to integrate dynamic performance information into the systems analysis. The ability to evaluate the dynamic performance of an engine design may allow tradeoffs between the dynamic performance and operability of a design resulting in a more efficient engine design. The second presentation discusses the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a Simulation system with a library containing the basic building blocks that can be used to create dynamic Thermodynamic Systems. Some of the key features include Turbo machinery components, such as turbines, compressors, etc., and basic control system blocks. T-MAT is written in the Matlab-Simulink environment and is open source software. The third presentation focuses on getting additional performance from the engine by allowing the limit regulators only to be active when a limit is danger of being violated. Typical aircraft engine control architecture is based on MINMAX scheme, which is designed to keep engine operating within prescribed mechanical/operational safety limits. Using a conditionally active min-max limit regulator scheme, additional performance can be gained by disabling non-relevant limit regulators

control↗

Very low frequency suspension systems for dynamic testing

Specifications for a Space Station suspension system which can provide rigid-body translation frequencies on the order of 0.1-0.2 Hz for a 50-foot payload weighing about 3400 lb and having a number of highly flexible appendages are discussed. Two suspension devices are considered, an all-mechanical passive device based on coil springs and a device using a combination of a passive pneumatic system and an active electromagnetic system. Test results show that both devices meet the initial requirements.

Kienholz, David A.↗

Global Load Balancing with Parallel Mesh Adaption on Distributed-Memory Systems

Dynamic mesh adaption on unstructured grids is a powerful tool for efficiently computing unsteady problems to resolve solution features of interest. Unfortunately, this causes load imbalance among processors on a parallel machine. This paper describes the parallel implementation of a tetrahedral mesh adaption scheme and a new global load balancing method. A heuristic remapping algorithm is presented that assigns partitions to processors such that the redistribution cost is minimized. Results indicate that the parallel performance of the mesh adaption code depends on the nature of the adaption region and show a 35.5X speedup on 64 processors of an SP2 when 35% of the mesh is randomly adapted. For large-scale scientific computations, our load balancing strategy gives almost a sixfold reduction in solver execution times over non-balanced loads. Furthermore, our heuristic remapper yields processor assignments that are less than 3% off the optimal solutions but requires only 1% of the computational time.

Biswas, Rupak↗

Global Load Balancing with Parallel Mesh Adaption on Distributed-Memory Systems

Dynamic mesh adaptation on unstructured grids is a powerful tool for efficiently computing unsteady problems to resolve solution features of interest. Unfortunately, this causes load inbalances among processors on a parallel machine. This paper described the parallel implementation of a tetrahedral mesh adaption scheme and a new global load balancing method. A heuristic remapping algorithm is presented that assigns partitions to processors such that the redistribution coast is minimized. Results indicate that the parallel performance of the mesh adaption code depends on the nature of the adaption region and show a 35.5X speedup on 64 processors of an SP2 when 35 percent of the mesh is randomly adapted. For large scale scientific computations, our load balancing strategy gives an almost sixfold reduction in solver execution times over non-balanced loads. Furthermore, our heuristic remappier yields processor assignments that are less than 3 percent of the optimal solutions, but requires only 1 percent of the computational time.

Biswas, Rupak↗

Large-scale systems: Complexity, stability, reliability

After showing that a complex dynamic system with a competitive structure has highly reliable stability, a class of noncompetitive dynamic systems for which competitive models can be constructed is defined. It is shown that such a construction is possible in the context of the hierarchic stability analysis. The scheme is based on the comparison principle and vector Liapunov functions.

Siljak, D. D.↗

Dynamic Isotope Surface Power Systems

The Dynamic Isotope Power Systems (DIPS) demonstration program, sponsored by the U.S. Department of Energy (DOE) with support funding from the National Aeronautics and Space Administration (NASA), is currently focused on the development of a standardized 2.5 kWe portable generator for multiple applications on the lunar or Martian surface. A variety of potential remote and mobile applications has been identified by NASA including surface rovers for both short and extended duration missions, remote power to science packages, and backup to central base power. Recent work focused on refining the 2.5 kWe design including assessing compatibility with the Martian environment to assure the design is suitable while imposing only a minor mass penalty on lunar operations. Additional work included a study performed to compare the DIPS with regenerative fuel cell systems for lunar mobile and remote power systems. Power requirements were reviewed and a modular system chosen for the comparison. Finally, a plan and cycle schematic were generated for an early demonstration of a prototypic isotope power Brayton system using the Antarctic as the test bed.

Hunt, Maribeth E.↗

Component model reduction via the projection and assembly method

The problem of acquiring a simple but sufficiently accurate model of a dynamic system is made more difficult when the dynamic system of interest is a multibody system comprised of several components. A low order system model may be created by reducing the order of the component models and making use of various available multibody dynamics programs to assemble them into a system model. The difficulty is in choosing the reduced order component models to meet system level requirements. The projection and assembly method, proposed originally by Eke, solves this difficulty by forming the full order system model, performing model reduction at the the system level using system level requirements, and then projecting the desired modes onto the components for component level model reduction. The projection and assembly method is analyzed to show the conditions under which the desired modes are captured exactly; to the numerical precision of the algorithm.

Bernard, Douglas E.↗