Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cost function”

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.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

The effect of additional design parameters on the LQR based design of a control/structural system

A multiobjective cost function that includes a form of the standard LQR regulator cost and its partial variation with respect to the additional design parameters is presented in connection with the design of an orbiting control/structural system. Simple models of uniform solid and tubular beams are demonstrated with two typical additional payload masses, i.e., symmetrically distributed and asymmetrically distributed, with respect to the center of the beam. By regarding the transient response of pitch angle and free-free beam deformations in the orbital plane, the optimal outer diameter of the beam and all feedback control can be determined by numerical analysis with this multicriterial approach. It is concluded that the multicriteria design approach should give better results from both the structural designer's and the control designer's standpoints.

Bainum, Peter M.↗
NASA NTRS1976

A separation theorem for the stochastic sampled-data LQG problem

This paper considers the control of a continuous linear plant disturbed by white plant noise when the control is constrained to be a piecewise constant function of time; i.e. a stochastic sampled-data system. The cost function is the integral of quadratic error terms in the state and control, thus penalizing errors at every instant of time while the plant noise disturbs the system continuously. The problem is solved by reducing the constrained continuous problem to an unconstrained discrete one. It is shown that the separation principle for estimation and control still holds for this problem when the plant disturbance and measurement noise are Gaussian.

Halyo, N.↗
NASA NTRS1978

A study of parameter identification

A set of definitions for deterministic parameter identification ability were proposed. Deterministic parameter identificability properties are presented based on four system characteristics: direct parameter recoverability, properties of the system transfer function, properties of output distinguishability, and uniqueness properties of a quadratic cost functional. Stochastic parameter identifiability was defined in terms of the existence of an estimation sequence for the unknown parameters which is consistent in probability. Stochastic parameter identifiability properties are presented based on the following characteristics: convergence properties of the maximum likelihood estimate, properties of the joint probability density functions of the observations, and properties of the information matrix.

Herget, C. J.↗
NASA NTRS1989

An algorithm for the solution of dynamic linear programs

The algorithm's objective is to efficiently solve Dynamic Linear Programs (DLP) by taking advantage of their special staircase structure. This algorithm constitutes a stepping stone to an improved algorithm for solving Dynamic Quadratic Programs, which, in turn, would make the nonlinear programming method of Successive Quadratic Programs more practical for solving trajectory optimization problems. The ultimate goal is to being trajectory optimization solution speeds into the realm of real-time control. The algorithm exploits the staircase nature of the large constraint matrix of the equality-constrained DLPs encountered when solving inequality-constrained DLPs by an active set approach. A numerically-stable, staircase QL factorization of the staircase constraint matrix is carried out starting from its last rows and columns. The resulting recursion is like the time-varying Riccati equation from multi-stage LQR theory. The resulting factorization increases the efficiency of all of the typical LP solution operations over that of a dense matrix LP code. At the same time numerical stability is ensured. The algorithm also takes advantage of dynamic programming ideas about the cost-to-go by relaxing active pseudo constraints in a backwards sweeping process. This further decreases the cost per update of the LP rank-1 updating procedure, although it may result in more changes of the active set that if pseudo constraints were relaxed in a non-stagewise fashion. The usual stability of closed-loop Linear/Quadratic optimally-controlled systems, if it carries over to strictly linear cost functions, implies that the saving due to reduced factor update effort may outweigh the cost of an increased number of updates. An aerospace example is presented in which a ground-to-ground rocket's distance is maximized. This example demonstrates the applicability of this class of algorithms to aerospace guidance. It also sheds light on the efficacy of the proposed pseudo constraint relaxation scheme.

Psiaki, Mark L.↗
NASA NTRS1988

Placing dynamic sensors and actuators on flexible space structures

Input/Output Cost Analysis involves decompositions of the quadratic cost function into contributions from each stochastic input and each weighted output. In the past, these suboptimal cost decomposition methods of sensor and actuator selection (SAS) have been used to locate perfect (infinite bandwidth) sensor and actuators on large scale systems. This paper extends these ideas to the more practical case of imperfect actuators and sensors with dynamics of their own. NASA's SCOLE examples demonstrate that sensor and actuator dynamics affect the optimal selection and placement of sensors and actuators.

Norris, Gregory A.↗
NASA NTRS2016

Usable Translational Hand Controllers for NASA's Habitability Design Center

This summer I was given the opportunity to work at the Habitability Design Center (HDC). NASA Johnson Space Center's HDC is currently developing Cislunar and Mars spacecraft mockups. I contributed to this effort by designing from scratch low cost, functional translational hand controllers (THCs) that will be used in spacecraft mission simulation in low to medium fidelity exploration spacecraft mockups. This project fell under the category of mechatronics, a combination of mechanical, electrical, and computer engineering. Being an aerospace engineering student, I was out of my comfort zone. And that was a wonderful thing. The autonomy that my mentor, Dr. Robert Howard, allowed me gave me the opportunity to learn by trying, failing, and trying again. This project was not only a professional success for me, but a significant learning experience. I appreciated the freedom that I had to take the time to learn new things for myself rather than blindly follow instructions. I was the sole person working on this project, and was required to work independently to solve the many hardware and software challenges that the project entailed. I researched THCs that have been used on the ISS, the Space Shuttle, and the Orion MPVC and based my design off of these. I worked through many redesigns before finding an optimal configuration of the necessary mechanisms and electrical components for the THC. Once I had a functional hardware design, I dove into the challenge of getting an Arduino Uno, an extremely low cost and easily programmable microcontroller, to behave as a human interface device. The THCs I built needed to be able to integrate to a mission simulation designed by NASA's Graphics and Visualization Lab. This proved to be the most challenging aspect of the project. To accomplish this I learned how to change the firmware of the USB serial converter microcontroller. The process was very complicated as it involved multiple software programs and manual flashing of pins on the Arduino itself. When I successfully achieved the goal I wrote an instructions manual for the process so that the HDC will be able to do this easily in the future for any human interface device they may want to create. I also created a detailed CAD model of my THC design with construction instructions. My THC utilizes three ultrasonic sensors, one for each axis of motion. I wrote a code that stimulates these sensors continuously and feeds back values from each axis ranging from -%100 to %100 of the min/max position in relation to the neutral position of each axis. This was the data that the Graphics and Visualization Lab required to interface with their simulation. I truly enjoyed working in the HDC surrounded by passionate, proactive, and brilliantly creative people. I felt valued and respected as a part of their team. I was given the time and support of my mentor whenever I asked for it. Beyond my positive project experience, I was fortunate enough to be able to take advantage of many of the extra activities that JSC has to offer. I took Russian Phase One during my lunch break every day and can now read Russian and accomplish basic verbal communication. I was heavily involved with the co-tern music video, which led to numerous incredible experiences and friendships. I saw every facility, attended every lecture, and met everyone that I could. I had coffee with Lauri Hansen. I played on an intern volleyball team at the Gilruth. I traveled to Michoud, Stennis, NOLA, and Big Bend National Park. I had the time of my life and I fell in love with JSC. In the next month I will return to Maryland and start my senior year of my undergraduate degree. As I work through it I will remember that all of the studying I do, all of the concentration I give, and all of the sacrifices that I make for school are so that I can work at a place like JSC where I am proud and excited to go into work every day. This internship was an invaluable experience for me, both professionally and personally.

Westbrook, Kimberly↗
NASA NTRS1975

Deterministic optimal maneuver strategy for multi-target missions

This paper presents an optimal strategy for making impulsive correction to a multi-target trajectory by a single maneuver. The concept of an optimal maneuver time is introduced. The choice of suitable weighting functions is explored to enable one to properly translate the subjective desire of mission success into an objective cost function whose minimization yields the optimal strategy. It is shown that a number of strategies previously formulated are derivable from one general expression. A number of other interesting properties of the optimal strategy are described. Numerical results are presented for a typical two-target mission. It is shown that the strategy formulated is optimal. For some perturbations, there exists an optimal maneuver time different from the time of initiation of the perturbation. That is, the physical properties of the trajectory can be exploited to select the optimal time of making a corrective maneuver.

Dwivedi, N. P.↗
NASA NTRS2011

Feature Acquisition with Imbalanced Training Data

This work considers cost-sensitive feature acquisition that attempts to classify a candidate datapoint from incomplete information. In this task, an agent acquires features of the datapoint using one or more costly diagnostic tests, and eventually ascribes a classification label. A cost function describes both the penalties for feature acquisition, as well as misclassification errors. A common solution is a Cost Sensitive Decision Tree (CSDT), a branching sequence of tests with features acquired at interior decision points and class assignment at the leaves. CSDT's can incorporate a wide range of diagnostic tests and can reflect arbitrary cost structures. They are particularly useful for online applications due to their low computational overhead. In this innovation, CSDT's are applied to cost-sensitive feature acquisition where the goal is to recognize very rare or unique phenomena in real time. Example applications from this domain include four areas. In stream processing, one seeks unique events in a real time data stream that is too large to store. In fault protection, a system must adapt quickly to react to anticipated errors by triggering repair activities or follow- up diagnostics. With real-time sensor networks, one seeks to classify unique, new events as they occur. With observational sciences, a new generation of instrumentation seeks unique events through online analysis of large observational datasets. This work presents a solution based on transfer learning principles that permits principled CSDT learning while exploiting any prior knowledge of the designer to correct both between-class and withinclass imbalance. Training examples are adaptively reweighted based on a decomposition of the data attributes. The result is a new, nonparametric representation that matches the anticipated attribute distribution for the target events.

Thompson, David R.↗
NASA NTRS2015

Phase-Based Adaptive Estimation of Magnitude-Squared Coherence Between Turbofan Internal Sensors and Far-Field Microphone Signals

A cross-power spectrum phase based adaptive technique is discussed which iteratively determines the time delay between two digitized signals that are coherent. The adaptive delay algorithm belongs to a class of algorithms that identifies a minimum of a pattern matching function. The algorithm uses a gradient technique to find the value of the adaptive delay that minimizes a cost function based in part on the slope of a linear function that fits the measured cross power spectrum phase and in part on the standard error of the curve fit. This procedure is applied to data from a Honeywell TECH977 static-engine test. Data was obtained using a combustor probe, two turbine exit probes, and far-field microphones. Signals from this instrumentation are used estimate the post-combustion residence time in the combustor. Comparison with previous studies of the post-combustion residence time validates this approach. In addition, the procedure removes the bias due to misalignment of signals in the calculation of coherence which is a first step in applying array processing methods to the magnitude squared coherence data. The procedure also provides an estimate of the cross-spectrum phase-offset.

Combustion↗
NASA NTRS1982

Time Domain Identification of an Optimal Control Pilot Model with Emphasis on the Objective Function

A method for the identification of the pilot's control compensation using time domain techniques is proposed. From this information we hope to infer a quadratic cost function, supported by the data, that represents a reasonable expression for the pilot's control objective in the task being performed, or an inferred piloting strategy. The objectives for this method are: (1) obtain a better understanding of the fundamental piloting techniques in complex tasks, such as landing approach; (2) the development of a metric measurable in simulations and flight test that correlate with subjective pilot opinion; and (3) to further validate pilot models and pilot vehicle analysis methods.

Schmidt, D. K.↗
NASA NTRS1972

Optimal trajectory generation for mechanical arms

A general method of generating optimal trajectories between an initial and a final position of an n degree of freedom manipulator arm with nonlinear equations of motion is proposed. The method is based on the assumption that the time history of each of the coordinates can be expanded in a series of simple time functions. By searching over the coefficients of the terms in the expansion, trajectories which minimize the value of a given cost function can be obtained. The method has been applied to a planar three degree of freedom arm.

Iemenschot, J. A.↗
NASA NTRS1981

On incorporating reliability considerations into control system designs

This paper considers reliability in designing control systems for large orbital structures that are expected to have appreciable flexibility. Reliability is considered for both the control configuration (i.e. selecting sensor and actuator locations over an admissible set) and the ultimate operation of the system. The approach presented is to construct a cost function that indicates the absolute goal of the system and, for a given structural design, to determine the lowest achievable costs conditioned on the failure states of the system (i.e. which actuators and sensors are operational). These costs are then weighted and summed to provide an overall system performance measure. This measure is then minimized over the set of admissible control configurations. The approach is illustrated using a beam that has four actuators with the goal of achieving a given parabolic shape.

Montgomery, R. C.↗
NASA NTRS2011

JWST Wavefront Control Toolbox

A Matlab-based toolbox has been developed for the wavefront control and optimization of segmented optical surfaces to correct for possible misalignments of James Webb Space Telescope (JWST) using influence functions. The toolbox employs both iterative and non-iterative methods to converge to an optimal solution by minimizing the cost function. The toolbox could be used in either of constrained and unconstrained optimizations. The control process involves 1 to 7 degrees-of-freedom perturbations per segment of primary mirror in addition to the 5 degrees of freedom of secondary mirror. The toolbox consists of a series of Matlab/Simulink functions and modules, developed based on a "wrapper" approach, that handles the interface and data flow between existing commercial optical modeling software packages such as Zemax and Code V. The limitations of the algorithm are dictated by the constraints of the moving parts in the mirrors.

Shin, Shahram Ron↗
NASA NTRS1986

Optimal control laws for microburst encounter

Simplified structures for longitudinal control laws that reduce an aircraft's response to the strong head-tailwind and downdraft variations associated with microbursts are presented. They are based on non-zero-set-point linear-quadratic regulators that command throttle setting and angle of attack as functions of velocity and flight path angle, and they can incorporate direct measurements of the wind profile if available. Selection of cost functions to be minimized by feedback control has been aided by a prior study of classical control laws and exact nonlinear-optimal flight paths through realistic microburst wind profiles. The resulting optimal control laws have an adaptive, dual-mode structure that can be implemented either in flight-director logic or in an autopilot.

Stengel, R. F.↗
NASA NTRS1990

Model reduction by weighted Component Cost Analysis

Component Cost Analysis considers any given system driven by a white noise process as an interconnection of different components, and assigns a metric called 'component cost' to each component. These component costs measure the contribution of each component to a predefined quadratic cost function. A reduced-order model of the given system may be obtained by deleting those components that have the smallest component costs. The theory of Component Cost Analysis is extended to include finite-bandwidth colored noises. The results also apply when actuators have dynamics of their own. Closed-form analytical expressions of component costs are also derived for a mechanical system described by its modal data. This is very useful to compute the modal costs of very high order systems. A numerical example for MINIMAST system is presented.

Kim, Jae H.↗
NASA NTRS2022

Towards Finding Energy Efficient Paths for Hybrid Airships in the Atmosphere of Venus

This paper presents a solution to the motion planning problem for an autonomous airship under superrotation winds of the Venusian atmosphere. The airship uses both buoyancy and aerodynamic lift to control its altitude. In addition, solar panels distributed over the aircraft provide energy to the propellers and allow for battery recharging. Our approach uses a sampling-based planner that relies on Dubins’ Airplane paths deformed under the influence of the winds to create a tree of kinematically feasible trajectories. We use the battery state to prune energetically unfeasible trajectories and we propose a cost function that accounts for the energy expenditure of the propulsive system and that considers battery charging by using the Economics notion of opportunity cost. The method is illustrated through a series of simulations that show how the vehicle takes longer and high-altitude paths to minimize the use of energy and favor battery recharge. Our results also show that naive trajectories are not feasible in terms of energy, justifying the need for more efficient solutions.

Bernardo Martinez R. Jr↗
NASA NTRS1971

Ride comfort control in large flexible aircraft

The problem of ameliorating the discomfort of passengers on a large air transport subject to flight disturbances is examined. The longitudinal dynamics of the aircraft, including effects of body flexing, are developed in terms of linear, constant coefficient differential equations in state variables. A cost functional, penalizing the rigid body displacements and flexure accelerations over the surface of the aircraft is formulated as a quadratic form. The resulting control problem, to minimize the cost subject to the state equation constraints, is of a class whose solutions are well known. The feedback gains for the optimal controller are calculated digitally, and the resulting autopilot is simulated on an analog computer and its performance evaluated.

Warren, M. E.↗