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At least 919 records · Page 51

Model Predictive Optimal Control of a Time-Delay Distributed-Parameter Systems

This paper presents an optimal control method for a class of distributed-parameter systems governed by first order, quasilinear hyperbolic partial differential equations that arise in many physical systems. Such systems are characterized by time delays since information is transported from one state to another by wave propagation. A general closed-loop hyperbolic transport model is controlled by a boundary control embedded in a periodic boundary condition. The boundary control is subject to a nonlinear differential equation constraint that models actuator dynamics of the system. The hyperbolic equation is thus coupled with the ordinary differential equation via the boundary condition. Optimality of this coupled system is investigated using variational principles to seek an adjoint formulation of the optimal control problem. The results are then applied to implement a model predictive control design for a wind tunnel to eliminate a transport delay effect that causes a poor Mach number regulation.

Nguyen, Nhan↗

Application of digital computer APU modeling techniques to control system design.

Study of the required controls for a H2-O2 auxiliary power unit (APU) technology program for the Space Shuttle. A steady-state system digital computer program was prepared and used to optimize initial system design. Analytical models of each system component were included. The program was used to solve a nineteen-dimensional problem, and then time-dependent differential equations were added to the computer program to simulate transient APU system and control. Some system parameters were considered quasi-steady-state, and others were treated as differential variables. The dynamic control analysis proceeded from initial ideal control modeling (which considered one control function and assumed the others to be ideal), stepwise through the system (adding control functions), until all of the control functions and their interactions were considered. In this way, the adequacy of the final control design over the required wide range of APU operating conditions was established.

Bailey, D. A.↗

SEASAT economic assessment. Volume 1: Summary and conclusions

A summary is presented of the economic benefits that can be derived from using the SEASAT Satellite System. A statement of the major findings of case studies of the practical applications of the SEASAT program to the following areas is given: (1) offshore oil and natural gas industry, (2) ocean mining, (3) coastal zones, (4) oil exploration in Arctic regions, (5) ocean fishing, and (6) ports and harbors. Also given is a description of the SEASAT System and its performance. A computer program, used to optimize SEASAT System's costs and operational requirements, is also considered.

Source record↗

System studies of coal fired-closed cycle MHD for central station power plants

This paper presents a discussion of the closed cycle MHD results obtained in a recent study of various advanced energy conversion (ECAS) power systems. The study was part of the first phase of this ECAS study. Since this was the first opportunity to evaluate the coal fired closed cycle MHD system, a number of iterations were required to partially optimize the system. The present paper deals with the latter part of the study in which the direct coal fired, MHD topping-steam bottoming cycle was established as the current choice for central station power generation. The emphasis of the paper is on the background assumptions and the conclusions that can be drawn from the closed cycle MHD analysis. The author concludes that closed cycle MHD has efficiencies comparable to that of open cycle MHD and that both systems are considerably more efficient than the other system studies in Phase 1 of the GE ECAS. Its cost will possibly be slightly higher than that of the open cycle MHD system. Also, with reasonable fuel escalation assumptions, both systems can produce lower cost electricity than conventional steam power plants. Suggestions for further work in closed cycle MHD components and systems is made.

Zauderer, B.↗

Use of a 35mm camera for remote surface cleanliness verification

Non-contact or remote monitoring of surfaces for both particle and molecular contaminants is required for verification of surface cleanliness on many program subsystems. The capability of a 35mm camera to satisfy this need is presented. The many limitations imposed by standard available lens systems are compared to actual required sensitivities. Methods of optimizing camera systems for specific applications and descriptions of support systems for extending the range of usefulness of the recorded data are also provided. Although this general concept is not new, significant improvements in the technique involving the use of polarized light and diffraction effects have resulted in a more efficient utilization of information recorded on the film.

Crutcher, E. R.↗

Sensitivity of Maize Yield in Smallholder Systems to Climate Scenarios in Semi-Arid Regions of West Africa: Accounting for Variability in Farm Management Practices

Climate change is estimated to exacerbate existing challenges faced by smallholder farmers in Sub-Sahara Africa. However, limited studies quantify the extent of variation in climate change impact under these systems at the local scale. The Decision Support System for Agro-technological Transfer (DSSAT) was used to quantify variation in climate change impacts on maize yield under current agricultural practices in semi-arid regions of Senegal (Nioro du Rip) and Ghana (Navrongo and Tamale). Multi-benchmark climate models (Mid-Century, 2040–2069 for two Representative Concentration Pathways, RCP4.5 and RCP8.5), and multiple soil and management information from agronomic surveys were used as input for DSSAT. The average impact of climate scenarios on grain yield among farms ranged between −9% and −39% across sites. Substantial variation in climate response exists across farms in the same farming zone with relative standard deviations from 8% to 117% at Nioro du Rip, 13% to 64% in Navrongo and 9% to 37% in Tamale across climate models. Variations in fertilizer application, planting dates and soil types explained the variation in the impact among farms. This study provides insight into the complexities of the impact of climate scenarios on maize yield and the need for better representation of heterogeneous farming systems for optimized outcomes in adaptation and resilience planning in smallholder systems.

Freduah, Bright S.↗

Rapid Lightweight Firmware Architecture of the Mobile Metamaterial Internal Co-Integrator Robot

The Mobile Metamaterial Internal Co-Integrator (MMIC-I) is a structure assembly and servicing robot for in-space servicing, assembly, and manufacturing of primary structures and infrastructure. MMIC-I is a battery-powered crawling robot that can travel through periodic structures such as trusses and open framework mechanical metamaterials. It does this through sequences of component extension, contraction, and gripping. This paper provides a detailed discussion of MMIC-I’s lightweight and rapidly developed firmware architecture, to enable demonstration of robot locomotion, secondary operations, and communications with a central command source. The rationale for the lightweight rapid development approach is to allow for assessment of long term system requirements in parallel with the mechatronics development, including optimization of system and subsystem power densities, to inform a future choice of flight ready software frameworks. MMIC-I system computing and I/O requirements are much lower than what is provided by proven baseline computing hardware for existing flight ready software frameworks such as the core Flight System, F prime, and the Robot Operating System. Development of earth gravity ground demonstration of the robotic systems is greatly benefited by limited power and mass factors for computing hardware. Here, we implement inter-process communication, commanding, and telemetry with the Espressif ESP32 module running the Arduino OS.

Damiana Catanoso↗

Optimality study of a gust alleviation system for light wing-loading STOL aircraft

An analytical study was made of an optimal gust alleviation system that employs a vertical gust sensor mounted forward of an aircraft's center of gravity. Frequency domain optimization techniques were employed to synthesize the optimal filters that process the corrective signals to the flaps and elevator actuators. Special attention was given to evaluating the effectiveness of lead time, that is, the time by which relative wind sensor information should lead the actual encounter of the gust. The resulting filter is expressed as an implicit function of the prescribed control cost. A numerical example for a light wing loading STOL aircraft is included in which the optimal trade-off between performance and control cost is systematically studied.

Komoda, M.↗

Multi-Stage System for Automatic Target Recognition

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Chao, Tien-Hsin↗

Synthesis of Optimal Nonlinear Feedback Laws for Dynamic Systems Using Neural Networks

Open-loop solutions of dynamical optimization problems can be numerically computed usingexisting software packages. The computed time histories of the state and control variables, formultiple sets of end conditions can then be used to train a neural network to 'recognize' the optimal,nonlinear feedback relation between the states and controls of the system. The 'learned' network canthen be used to output an approximate optimal control given a full set (or a partial set) of measuredsystem states. With simple neural networks, we have successfully demonstrated the efficacy of theproposed approach using a minimum-time orbit injection problem. The usefulness and limitations ofthis novel approach on real-life optimal guidance and control problems, with many state and control variables as well as path inequality constraints, remain to be seen.

Orbit injection problem↗

Robustified time-optimal control of uncertain structural dynamic systems

A new approach for computing open-loop time-optimal control inputs for uncertain linear dynamical systems is developed. In particular, the single-axis, rest-to-rest maneuvering problem of flexible spacecraft in the presence of uncertainty in model parameters is considered. Robustified time-optimal control inputs are obtained by solving a parameter optimization problem subject to robustness constraints. A simple dynamical system with a rigid-body mode and one flexible mode is used to illustrate the concept.

Liu, Qiang↗

Guidance, Navigation, and Control System Design in a Mass Reduction Exercise

Early Orion GN&C system designs optimized for robustness, simplicity, and utilization of commercially available components. During the System Definition Review (SDR), all subsystems on Orion were asked to re-optimize with component mass and steady state power as primary design metrics. The objective was to create a mass reserve in the Orion point of departure vehicle design prior to beginning the PDR analysis cycle. The Orion GN&C subsystem team transitioned from a philosophy of absolute 2 fault tolerance for crew safety and 1 fault tolerance for mission success to an approach of 1 fault tolerance for crew safety and risk based redundancy to meet probability allocations of loss of mission and loss of crew. This paper will discuss the analyses, rationale, and end results of this activity regarding Orion navigation sensor hardware, control effectors, and trajectory design.

Crain, Timothy↗