SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
This paper considers the suboptimal stochastic control of linear discrete-time dynamical systems with unknown or stochastically varying parameters. The suboptimal scheme is based upon the use of the open-loop-feedback-optimal (O.L.F.O.) method. The state and parameter estimates are generated by an extended Kalman filter algorithm. Numerical results for first order systems are presented.
This paper considers the suboptimal stochastic control of linear discrete-time dynamical systems with uncertain or stochastically varying parameters. The suboptimal scheme is based upon the use of the open-loop-feedback-optimal (OLFO) method. The state and parameter estimates are generated by an extended Kalman filter algorithm. Numerical results for first-order systems are presented.
In this paper digital learning control methods are developed primarily for use in single-input, single-output nonlinear dynamic systems. Conditions for convergence of the basic form of learning control based on integral control concepts are given, and shown to be satisfied by a large class of nonlinear problems. It is shown that it is not the gross nonlinearities of the differential equations that matter in the convergence, but rather the much smaller nonlinearities that can manifest themselves during the short time interval of one sample time. New algorithms are developed that eliminate restrictions on the size of the learning gain, and on knowledge of the appropriate sign of the learning gain, for convergence to zero error in tracking a feasible desired output trajectory. It is shown that one of the new algorithms can give guaranteed convergence in the presence of actuator saturation constraints, and indicate when the requested trajectory is beyond the actuator capabilities.
Chemical transformations in aerosols impact the lifetime of particle phase species, the fate of atmospheric pollutants, and both climate- and health-relevant aerosol properties. Timescales for multiphase reactions of ozone in atmospheric aqueous phases are governed by coupled kinetic processes between the gas phase, the particle interface, and its bulk, which respond dynamically to reactive consumption of O 3 . However, models of atmospheric aerosol reactivity often do not account for the coupled nature of multiphase processes. Herein, to examine these dynamics, we use new and prior experimental observations of aqueous droplet reaction kinetics, including three systems with a range of surface affinities and ozonolysis rate coefficients ( trans -aconitic acid (C 6 H 6 O 6 ), maleic acid (C 4 H 4 O 4 ), and sodium nitrite (NaNO 2 )). Using literature rate coefficients and thermodynamic properties, we constrain a simple two-compartment stochastic kinetic model which resolves the interface from the particle bulk and represents O 3 partitioning, diffusion, and reaction as a coupled kinetic system. Our kinetic model accurately predicts decay kinetics across all three systems, demonstrating that both the thermodynamic properties of O 3 and the coupled kinetic and diffusion processes are key to making accurate predictions. An enhanced concentration of adsorbed O 3 , compared to gas and bulk phases is rapidly maintained and remains constant even as O 3 is consumed by reaction. Multiphase systems dynamically seek to achieve equilibrium in response to reactive O 3 loss, but this is hampered at solute concentrations relevant to aqueous aerosol by the rate of O 3 arrival in the bulk by diffusion. As a result, bulk-phase O 3 becomes depleted from its Henry's law solubility. This bulk-phase O 3 depletion limits reaction timescales for relatively slow-reacting organic solutes with low interfacial affinity (i.e., trans-aconitic and maleic acids, with k rxn ≈ 10 3 -10 4 M -1 s -1 ), which is in contrast to fast-reacting solutes with higher surface affinity (i.e., nitrite, with k rxn ≈ 10 5 M -1 s -1 ) where surface reactions strongly impact the observed decay kinetics.
A variety of autonomous oscillations in nature such as heartbeats and some biochemical reactions have been widely studied and utilized for applications in the fields of bioscience and engineering. Here, we report a unique phenomenon of moisture-induced electrical potential oscillations on polymers, poly([2-(methacryloyloxy)ethyl] dimethyl-(3-sulfopropyl) ammonium hydroxide-co-acrylic acid), during the diffusion of water molecules. Chemical reactions are modeled by kinetic simulations while system dynamic equations and the stability matrix are analyzed to show the chaotic nature of the system which oscillates with hidden attractors to induce the autonomous surface potential oscillation. Using moisture in the ambient environment as the activation source, this self-excited chemoelectrical reaction could have broad influences and usages in surface-reaction based devices and systems. As a proof-of-concept demonstration, an energy harvester is constructed and achieved the continuous energy production for more than 15,000 seconds with an energy density of 16.8 mJ/cm 2 . A 2-Volts output voltage has been produced to power a liquid crystal display toward practical applications with five energy harvesters connected in series.
Power system dynamics will be significantly changed by integrating wind farms and solar photovoltaic plants into power systems. This study investigates the effect of momentary cessation of inverter-based resources (IBRs) on transient stability and provides a recovery strategy for bulk IBRs in power systems. The theoretical analysis was initially carried out on a one-machine infinite-bus system, demonstrating the IBR impact in a critical group. The analysis was then expanded to a multimachine power system with IBRs using the single-machine equivalent method. The study found that IBRs in critical and noncritical groups exert contrasting effects on transient stability. Finally, a strategy for enhancing transient stability is proposed by controlling IBRs during power system recovery. The proposed strategy was verified by simulation on IEEE 9-bus and IEEE 39-bus power systems with the addition of IBRs. A 39-bus power system simulation demonstrates the scalability of the proposed method. Here, the proposed strategy provides effective and executable measures for improving system security in the presence of IBRs.
Power system dynamic stability can be evaluated through the analysis of transient oscillations that occur following significant system events. One of the earliest methods for this type of study is Prony analysis, which estimates the system's electromechanical modes. While previous studies have highlighted advantages of performing Prony analysis on data in the forward and backward directions, the proposed method does so simultaneously. As a result, signal poles corresponding to electromechanical modes can be distinguished from spurious poles more reliably. The method also produces a single mode estimate, where independent application in the forward and backward directions would produce two estimates for each mode. The method is validated using simulated and measured power system data.
Major results from the frequency analysis of system program (FASP) are reported. The FASP procedure was designed to analyze or design linear dynamic systems, but can be used to solve any problem that can be described by a system of linear time invariant differential equations. The program also shows plots of performance changes as design parameters are adjusted. Experimental results on narrowband FM distortion are also reported.
An analysis of the flight dynamics and piloted control characteristics of the Helistat, a quadrotor heavy-lift airship, was completed using the HYBRDS airship simulation facility. The analysis covered the full operating flight envelope, including likely ranges of altitude, airspeed, sideslip, and loading variations. Particular areas of study were performance, trim, power requirements, linearized dynamics, handling qualities, and mooring operations. The key assumptions were: a rigid vehicle, no control system dynamics, fixed rotor and propeller RPM, and no ballonet dynamics. The nominal cruise speed for the H34 engines operating at 1275 HP was found to be 40-50 kts, depending on the loading condition. The maximum payload capability was calculated as 45,000 lbs for sea level-based operations. The crosswind capability in hover is 5-10 kts depending on the loading conditions, but this requires excessive roll angle due to the roll-to-translate control gearing. Sideslip angles of 110-135 degrees (wind from aft quarters) are critical for directional trim and stability, and should be avoided.
The User Manual for the Integrated Analysis Capability (IAC) Level 1 system is presented. The IAC system currently supports the thermal, structures, controls and system dynamics technologies, and its development is influenced by the requirements for design/analysis of large space systems. The system has many features which make it applicable to general problems in engineering, and to management of data and software. Information includes basic IAC operation, executive commands, modules, solution paths, data organization and storage, IAC utilities, and module implementation.
Control-theory design package, Optimal Regulator Algorithms for Control of Linear Systems (ORACLS), developed to aid in design of controllers and optimal filters for systems modeled by linear, time-invariant differential and difference equations. Optimal linear quadratic regulator theory, Linear-Quadratic-Gaussian (LQG) problem, most widely accepted method of determining optimal control policy. Provides for solution to time-in-variant continuous or discrete LQG problems. Attractive to control-system designer providing rigorous tool for dealing with multi-input and multi-output dynamic systems in continuous and discrete form. CDO version written in FORTRAN IV. VAX version written in FORTRAN 77.
The problem inherent to large scale systems such as power network, communication network and economic or ecological systems were studied. The increase in size and flexibility of future spacecraft has put those dynamical systems into the category of large scale systems, and tools specific to the class of large systems are being sought to design control systems that can guarantee more stability and better performance. Among several survey papers, reference was found to a thorough investigation on decentralized control methods. Especially helpful was the classification made of the different existing approaches to deal with large scale systems. A very similar classification is used, even though the papers surveyed are somehow different from the ones reviewed in other papers. Special attention is brought to the applicability of the existing methods to controlling large mechanical systems like large space structures. Some recent developments are added to this survey.
The specific purpose of the symposium was to familiarize the engineering structures community with the depth and range of research performed by the Structures Division of the Lewis Research Center and its academic and industrial partners. Sessions covered vibration control, fracture mechanics, ceramic component reliability, parallel computing, nondestructive testing, dynamical systems, fatigue and damage, wind turbines, hot section technology, structural mechanics codes, computational methods for dynamics, structural optimization, and applications of structural dynamics.
This paper presents a state-space approach for self-tuning control of a more general class of multivariable stochastic systems having a number of inputs equal or different from the number of outputs. The dynamic system is represented in the state-space innovation form with Luenberger's canonical structures. The model parameters and the Kalman gain are identified via either the extended least-squares algorithm or the least-squares ladder algorithm. The Kalman gain matrix and states can be estimated from the identified parameters without utilizing the standard state estimation algorithm. A long division method is introduced for finding the similarity transformation matrix.
The paper presents the results of an ICCS analysis focusing on discrete-time control systems subject to time-varying delays. The present analytical technique is applicable to integrated dynamic systems such as those encountered in advanced aircraft, spacecraft, and the real-time control of robots and machine tools via a high-speed network within an autonomous manufacturing environment. The significance of data latency and missynchronization between individual system components in ICCS networks is discussed in view of the time-varying delays.
Perturbation techniques used for identification of rotating system dynamic characteristics are described. A comparison between two periodic frequency-swept perturbation methods applied in identification of fluid forces of rotating machines is presented. The description of the fluid force model identified by inputting circular periodic frequency-swept force is given. This model is based on the existence and strength of the circumferential flow, most often generated by the shaft rotation. The application of the fluid force model in rotor dynamic analysis is presented. It is shown that the rotor stability is an entire rotating system property. Some areas for further research are discussed.
The Software Engineering Process Simulation (SEPS) model is described which was developed at JPL. SEPS is a dynamic simulation model of the software project development process. It uses the feedback principles of system dynamics to simulate the dynamic interactions among various software life cycle development activities and management decision making processes. The model is designed to be a planning tool to examine tradeoffs of cost, schedule, and functionality, and to test the implications of different managerial policies on a project's outcome. Furthermore, SEPS will enable software managers to gain a better understanding of the dynamics of software project development and perform postmodern assessments.
Archival RXTE ASM and PCA observations of the black hole binary LMC X-3 reveal a dramatic and extended low state lasting from December 8, 2003 until March 18, 2004, unprecedented both in its Low luminosity (Lx(2-10keV)=4.2x 1035 ergs s-1, approximately 4 times fainter than ever before seen from LMC X-3 in its low/hard state, and representing 0.15% of its X-ray luminosity during the high/soft state); and Long duration (approximately equal to 100 days, as compared with 5-20 days for 'normal' low/hard state excursions). During this anomalous low state no significant variability is observed on timescales of days-weeks, and the spectrum is well described by a simple power law with index 1.7 plus or minus 0.2. We examine the variability characteristics of LMC X-3 before and after this event using conventional and topological methods, and show that with the exception of the anomalous low state itself the long-term behavior of the source in topological phase space can be completely described in terms of a well-understood nonlinear dynamics system known as the Duffing oscillator, implying that the accretion disk in LMC X-3 is a driven, dissipative system with two solutions competing for control of its time evolution. This work shows that dynamical information and constraints revealed by topological analysis methods can provide a valuable addition to traditional studies of accretion disk behavior.