Sufficient conditions for the optimality of a stochastic control.
Sufficient conditions for optimal stochastic control of diffusion processes governed by vector equations satisfying local Lipschitz conditions
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Sufficient conditions for optimal stochastic control of diffusion processes governed by vector equations satisfying local Lipschitz conditions
Thermal hydraulic instability can challenge the control and the safety of nuclear reactors. This experimental research captures and investigates the instability in a low-pressure (1–10 atmospheres) natural circulation loop with an adiabatic chimney installed above the heated section. Direct transient local measurement of two-phase flow is performed at multiple axial locations along the flow channel with thermocouples and conductivity probes traversed by customized high-precision mechanisms. Based on the periodicity of oscillations, a post-processing method is proposed to align the data captured non-simultaneously to reconstruct the instability behavior in one representative period. The averaging operation over multiple oscillation cycles is performed to reduce the random errors. Cyclic phenomena are clearly demonstrated by the post-processed data, and rapid void fraction change induced by the flashing is observed to be significant in the driving mechanism for low pressure oscillations. Parametric effects of inlet subcooling, heat flux, inlet flow restriction and system pressure are studied within the experiment range, and qualitative results are explained and compared with existing literature. The ratio between the oscillation period and the travelling time of the fluid particle through the test section is compared with the theoretical value for the density wave oscillation. The new dataset contains directly measured transient multi-dimensional two-phase data along the flow channel for natural circulation under density wave oscillations. The generated dataset is valuable for the validation of system analysis codes and CFD codes in the simulation of natural circulation phenomena and dynamic two-phase flow.
A computer model was developed using actual wind time series and turbine performance data to simulate the power produced by the Sandia 17-m VAWT operating in automatic control. The model was used to investigate the influence of starting algorithms on annual energy production. The results indicate that, depending on turbine and local wind characteristics, a bad choice of a control algorithm can significantly reduce overall energy production. The model can be used to select control algorithms and threshold parameters that maximize long term energy production. The results from local site and turbine characteristics were generalized to obtain general guidelines for control algorithm design.
To increase quantified information about the effectiveness and subjective workload of force information relayed through manipulator input control devices, a space related task was performed by eight subjects with kinesthetic force feedback and/or local force accommodation through three different input control devices (i.e., hand controllers) operating in rate control mode. Task completion time, manipulator work, and subjective responses were measured. Results indicated a difference among the hand controllers. For the Honeywell six degree-of-freedom hand controller, the overall task completion times were shortest, the amount of work exerted was the least, and was the most preferred by test subjects. Neither force accommodation with or without reflection resulted in shorter task completion times or reduced work although those conditions were better than no force information for some aspects. Comparisons of results from previous studies are discussed.
Independently deflectable control surfaces are located on the trailing edge of the wing of a blended wing-body aircraft. The reconfiguration control system of the present invention controls the deflection of each control surface to optimize the spanwise lift distribution across the wing for each of several flight conditions, e.g., cruise, pitch maneuver, and high lift at low speed. The control surfaces are deflected and reconfigured to their predetermined optimal positions when the aircraft is in each of the aforementioned flight conditions. With respect to cruise, the reconfiguration control system will maximize the lift to drag ratio and keep the aircraft trimmed at a stable angle of attack. In a pitch maneuver, the control surfaces are deflected to pitch the aircraft and increase lift. Moreover, this increased lift has its spanwise center of pressure shifted inboard relative to its location for cruise. This inboard shifting reduces the increased bending moment about the aircraft's x-axis occasioned by the increased pitch force acting normal to the wing. To optimize high lift at low speed, during take-off and landing for example, the control surfaces are reconfigured to increase the local maximum coefficient of lift at stall-critical spanwise locations while providing pitch trim with control surfaces that are not stall critical.
Experience has shown that the flutter prediction process for airplanes can be greatly affected by strong concentrated nonlinearities which may be localized in the linking elements of the control mechanism, in the pivot joints of variable-sweep-wing systems, and in the connecting points between wing and pylon-mounted external stores. The principle of equivalent linearization offers an efficent possibility for solving the related nonlinear flutter equations in the frequency domain as a complement to the well-known time domain procedures. Taking as an example an airplane with nonlinear control characteristics, it is demonstrated how the equivalent linearization approach can be extended to rather complicated systems with multiple sets of strongly interacting, concentrated nonlinearities.
Anisotropy, the characteristic of materials exhibiting different properties based on their direction, is widespread in nature. Conventional manufacturing techniques often fall short in recreating such complex anisotropy. While 3D printing allows for precise fiber deposition in anisotropic composites, previous studies have only achieved bulk reorientation of fibers at the voxel level in two dimensions. This limits the replication of localized 3D anisotropies found in natural materials. To address this, a novel 3D printing technique is presented that enables subvoxel control of fiber orientation in all three directions using multidirectional shearing via nozzle rotation and inclination. The fiber orientation control in these experimental tests is driven by a numerical model, enabling a fully digital approach to program microstructures within a strand. This programmability is demonstrated through mechanical and thermal tests, illustrating a localized and controllable response to external stimuli. Achieving such complex anisotropy holds potential across several fields, including wearables and biomedical implants, lightweight composite structures, and energy storage technologies such as batteries and supercapacitors.
TMF is based on imposing a controlled phase-shift in a train of electromagnets, forming a stack. Thus, the induced magnetic field can be considered to be travelling along the axis of the stack. The coupling of this traveling wave with an electrically conducting fluid results in a basic flow in a form of a single axisymmetric roll. The magnitude and direction of this flow can be remotely controlled. Furthermore, it is possible to localize the effect of this force field though activating only a number of the magnets. This force field generated in the fluid can, in principle, be used to control and modify convection in the molten material. For example, it can be used to enhance convective mixing in the melt, and thereby modify the interface shape, and macrosegregation. Alternatively, it can be used to counteract thermal and/or solutal buoyancy forces. High frequency TMF can be used in containerless processing techniques, such as float zoning, to affect the very edge of the fluid so that Marangoni flow can be counter balanced. The proposed program consists of basic fundamentals and applications. Our goal in conducting the following experiments and analyses is to establish the validity of TMF as a new tool for solidification processes. Due to its low power consumption and simplicity of design, this tool may find wide spread use in a variety of space experiments. The proposed ground based experiments are intended to establish the advantages and limitations of employing this technique. In the fundamentals component of the proposed program, we will use theoretical tools and experiments with mercury to establish the fundamental aspects of TMF-induced convection through a detailed comparison of theoretical predictions and experimental measurements of flow field. In this work, we will conduct a detailed parametric study involving the effects of magnetic field strength, frequency, wave vector, and the fluid geometry. The applications component of this work will be focused on investigating the effect of TMF on the following solidification and pre-directional solidification processes: (1) Bridgman growth of Ga:Ge with the goal of counteracting the buoyancy-driven convection; (2) Mixing of Pb-Ga and Pb-Sn alloys with the aim of initiating and maintaining a uniform melt prior to solidification processing; and (3) Float Zone growth with the aim of identifying, through simulations and model experiments, conditions needed to counteract Marangoni flow in a microgravity environment. The proposed research has strong relevance to microgravity research and the objectives of the NRA. TMF can provide a unique and accurate mechanism for generation and control of desirable flow patterns for microgravity research. These attributes have significant relevance to 1) Alloy mixing prior to solidification in a microgravity environment. TMF can provide this mixing with a low level of power consumption; (2) TMF can offset the deleterious effects of Marangoni convection in microgravity containerless processing. Thus, TMF can be instrumental in further understanding this phenomena; (3) Generation of controlled flows will allow the investigation of the effect of these flows on growth morphology and growth kinetics; and (4) On Earth, TMF has the potential to significantly counter-balance thermosolutal convection, thereby creating conditions similar to those obtained in microgravity. Once demonstrated, this new tool for use in solidification has the strong potential to find applications in a host of microgravity material research projects.
A telerobotics system is described which provides supervised autonomous control capability for time-delayed ground-remote control applications. The system includes a local site operator interface for interactive task description and a remote site task execution system. Interactive stereo graphics overlay on video is provided at the local site to update the remote environmental model. The remote site system is capable of nominal task execution as well as monitoring and reflex action. Execution utilizes multiple control modules which execute based upon command parameterization.
A predictive, multiple model control strategy is developed based on an ensemble of local linear models of the nonlinear system dynamics for a transonic wind tunnel. The local linear models are estimated directly from the weights of a Self Organizing Feature Map (SOFM). Local linear modeling of nonlinear autonomous systems with the SOFM is extended to a control framework where the modeled system is nonautonomous, driven by an exogenous input. This extension to a control framework is based on the consideration of a finite number of subregions in the control space. Multiple self organizing feature maps collectively model the global response of the wind tunnel to a finite set of representative prototype controls. These prototype controls partition the control space and incorporate experimental knowledge gained from decades of operation. Each SOFM models the combination of the tunnel with one of the representative controls, over the entire range of operation. The SOFM based linear models are used to predict the tunnel response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal. Each SOFM provides a codebook representation of the tunnel dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the minimization of a similarity metric which is the essence of the self organizing feature of the map. Thus, the SOFM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme than selects the best available model for the applied control. Experimental results of controlling the wind tunnel, with the proposed method, during operational runs where strict research requirements on the control of the Mach number were met, are presented. Comparison to similar runs under the same conditions with the tunnel controlled by either the existing controller or an expert operator indicate the superiority of the method.
Metamaterials present the possibility of artificially generating advanced functionalities through engineering of their internal structure. Artificial spin networks, in which a large number of nanoscale magnetic elements are coupled together, are promising metamaterial candidates that enable the control of collective magnetic behavior through tuning of the local interaction between elements. In this work, the motion of magnetic domain-walls in an artificial spin network leads to a tunable stochastic response of the metamaterial, which can be tailored through an external magnetic field and local lattice modifications. This type of tunable stochastic network produces a controllable random response exploiting intrinsic stochasticity within magnetic domain-wall motion at the nanoscale. An iconic demonstration used to illustrate the control of randomness is the Galton board. In this system, multiple balls fall into an array of pegs to generate a bell-shaped curve that can be modified via the array spacing or the tilt of the board. A nanoscale recreation of this experiment using an artificial spin network is employed to demonstrate tunable stochasticity. Furthermore, this type of tunable stochastic network opens new paths toward post-Von Neumann computing architectures such as Bayesian sensing or random neural networks, in which stochasticity is harnessed to efficiently perform complex computational tasks.
Local site ordering offers a new paradigm for property control in functional materials. However, systems that exhibit a propensity for local order and global disorder are often challenging to characterize, and demonstrations of ordering-induced property tuning are few and far between. Here, we demonstrate that short-range ordering tunes the optical absorption edge in the long-range disordered alloy system (ZnSnN2)1-x(ZnO)2x at x = 0.25. We use combinatorial cosputtering to synthesize a set of thin-film samples spanning this alloy space. X-ray diffraction demonstrates lattice contraction as a function of alloy composition, confirming that a mixed-anion and -cation alloy has been synthesized. Using N and O K-edge X-ray absorption near-edge structure in conjunction with simulations of cation-disordered supercell structures, we find that samples exhibit octet-rule-breaking motifs around both anions. Upon annealing at an alloy composition of x = 0.25, X-ray absorption analysis suggests that local motif structure shifts toward octet-rule-conserving while long-range disorder is maintained. Spectroscopic ellipsometry reveals that local ordering increases the absorption edge energy at constant composition. Additionally, alloy-induced optical absorption edge tuning is demonstrated. This work paves the way toward property tuning with short-range ordering in (ZnSnN2)1-x(ZnO)2x and beyond.
This paper presents a hierarchical application of Discrete Event Supervisory (DES) control theory for intelligent decision and control of a twin-engine aircraft propulsion system. A dual layer hierarchical DES controller is designed to supervise and coordinate the operation of two engines of the propulsion system. The two engines are individually controlled to achieve enhanced performance and reliability, necessary for fulfilling the mission objectives. Each engine is operated under a continuously varying control system that maintains the specified performance and a local discrete-event supervisor for condition monitoring and life extending control. A global upper level DES controller is designed for load balancing and overall health management of the propulsion system.
This article presents a novel decentralized filtering adaptive neural network control framework for uncertain switched interconnected nonlinear systems. Each subsystem has its own decentralized controller based on the established decentralized state predictor. For each subsystem, the nonlinear uncertainties are approximated by a Gaussian radial basis function (GRBF) neural network incorporated with a piecewise constant adaptive law, where the adaptive law will update adaptive parameters from the error dynamics between the host system and the decentralized state predictor by discarding the unknowns, whereas a decentralized filtering control law is derived to cancel both local and mismatched uncertainties from other subsystems, as well as achieve the local objective tracking of the host system. The achievement of global objective depends on the achievement of local objective for each subsystem. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. By exploiting the average dwell time principle, the error bounds between the real system and the virtual reference system, which defines the best performance that can be achieved by the closed-loop system, are derived. A numerical example is given to illustrate the effectiveness of the decentralized filtering adaptive neural network control architecture by comparing against the model reference adaptive control (MRAC).
Flight reentry experiments define the total heating on a large blunt-nosed body by means of imbedded thermocouples. The thermocouples, installed in a beryllium layered forebody, were designed to provide minimum feasible disturbance of local heat flow with accurate depth control of the thermocouple junction locations.
We propose a trust-region method that solves a sequence of linear integer programs to tackle integer optimal control problems regularized with a total variation penalty. The total variation penalty implies that the considered integer control problems admit minimizers. We introduce a local optimality concept for the problem, which arises from the infinite-dimensional perspective. In the case of a one-dimensional domain of the control function, we prove convergence of the iterates produced by our algorithm to points that satisfy first-order stationarity conditions for local optimality. We demonstrate the theoretical findings on a computational example.
This report demonstrates tunable carrier densities in CdO thin films through local ion irradiation, providing lateral control of mid‐IR optical properties. Ion‐solid interactions produce donor‐like defects that boost electron concentrations from the practical minimum of 2.5 × 10 19 cm −3 to a maximum of 2.5 × 10 20 cm −3 by metered ion exposure. This range is achieved using He, N, Ar, or Au ions at 1–2.8 MeV; when normalized by displacements per atom, all ion species produce comparable results. Since CdO is well‐described by the Drude model, irradiation‐tuned carrier densities directly alter the infrared dielectric function, and in turn, mid‐infrared optical properties. Further, it is demonstrated that by combining irradiation with traditional lithography, CdO films expose to ions in the presence of 3‐µm thick, patterned photoresist exhibit lateral carrier density profiles with ≈400‐nm resolution. Scanning near‐field optical microscopy reveals sharp optical interfaces with almost no companion contrast in surface morphology, microstructure, or crystallinity. Finally, CdO lateral homostructures supporting surface plasmon polaritons (SPPs) are demonstrated whose dispersion relation can be tuned through periodic patterning in a monolithic platform by simple nanofabrication. Numerical simulations show these polaritons result from strong coupling between excitations at CdO plasma frequencies and SPPs supported by the platinum substrate.
The LAP07 multicenter randomized study assessed whether chemoradiation therapy increases overall survival versus continuation chemotherapy in patients whose locally advanced pancreatic cancer was controlled after 4 months of induction chemotherapy. This analysis investigated whether failure to adhere to radiation therapy (RT) guidelines influenced survival and toxicity.