Search NASA⌕ Search

SEARCH · Search NASA

Results for “approximate dynamic programming”

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 55 records · Page 3

Adaptive Optimization for System Performance and Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles

The emerging urban air mobility (UAM) sector in aerospace is driving development of unconventional multi-modal vehicle configurations and autonomous flight. The combination of multi-modal vehicle dynamics, complex environment, requirements to deal with flight contingencies in an efficient and safe manner, as well as necessity for precise trajectory following and performance, are the driving influence behind adaptive optimization for system performance. We are interested in trajectory optimization algorithm that would system parameter estimation and identifying the optimal switching time between modes of hybrid dynamical systems. This presentation discusses a parameterized optimal control trajectory optimization algorithm that is an extended and generalized version of Differential Dynamic Programming (DDP), titled Parameterized Differential Dynamic Programming (PDDP). DDP is an efficient trajectory optimization algorithm relying on second order approximations of a system’s dynamics and cost function and has recently been applied to optimize systems with time invariant parameters. Experiments are presented applying PDDP to solve model predictive control (MPC) and moving horizon estimation (MHE) tasks simultaneously. In particular, PDDP is used to determine the optimal transition point between flight regimes of a complex urban air mobility (UAM) class vehicle exhibiting multiple phases of flight and to identify and compensate for actuation faults.

optimization↗

Multistage distributionally robust mixed-integer programming with decision-dependent moment-based ambiguity sets

We study multistage distributionally robust mixed-integer programs under endogenous uncertainty, where the probability distribution of stage-wise uncertainty depends on the decisions made in previous stages. We first consider two ambiguity sets defined by decision-dependent bounds on the first and second moments of uncertain parameters and by mean and covariance matrix that exactly match decision-dependent empirical ones, respectively. For both sets, we show that the subproblem in each stage can be recast as a mixed-integer linear program (MILP). Moreover, we extend the general moment-based ambiguity set in to the multistage decision-dependent setting, and derive mixed-integer semidefinite programming (MISDP) reformulations of stage-wise subproblems. We develop methods for attaining lower and upper bounds of the optimal objective value of the multistage MISDPs, and approximate them using a series of MILPs. We deploy the Stochastic Dual Dynamic integer Programming (SDDiP) method for solving the problem under the three ambiguity sets with risk-neutral or risk-averse objective functions, and conduct numerical studies on multistage facility-location instances having diverse sizes under different parameter and uncertainty settings. Furthermore, our results show that the SDDiP quickly finds optimal solutions for moderate-sized instances under the first two ambiguity sets, and also finds good approximate bounds for the multistage MISDPs derived under the third ambiguity set. We also demonstrate the efficacy of incorporating decision-dependent distributional ambiguity in multistage decision-making processes.

97 MATHEMATICS AND COMPUTING↗

Towards a general object-oriented software development methodology

An object is an abstract software model of a problem domain entity. Objects are packages of both data and operations of that data (Goldberg 83, Booch 83). The Ada (tm) package construct is representative of this general notion of an object. Object-oriented design is the technique of using objects as the basic unit of modularity in systems design. The Software Engineering Laboratory at the Goddard Space Flight Center is currently involved in a pilot program to develop a flight dynamics simulator in Ada (approximately 40,000 statements) using object-oriented methods. Several authors have applied object-oriented concepts to Ada (e.g., Booch 83, Cherry 85). It was found that these methodologies are limited. As a result a more general approach was synthesized with allows a designer to apply powerful object-oriented principles to a wide range of applications and at all stages of design. An overview is provided of this approach. Further, how object-oriented design fits into the overall software life-cycle is considered.

Seidewitz, ED↗

Method for compression testing of composite materials at high strain rates

A method is presented for testing composite materials in compression at strain rates up to approximately 500 per s. The method uses a thin ring specimen (4 in. in diameter, 1 in. wide, six-eight plies thick) loaded dynamically by an external pressure pulse applied explosively through a liquid. Strains in the specimen and in a steel calibration ring are recoorded with a digital processing oscilloscope. Results are plotted by an x-y plotter in the form of a dynamic stress-strain curve. Data analysis is based on a numerical solution of the equation of motion. A computer program is used which involves smoothing and approximation of the strain magnitude, strain rate, and strain acceleration. Dynamic stress-strain curves obtained for 0-deg and 90-deg specimens of two graphite/epoxy composites are presented.

Daniel, I. M.↗

Generalized Newton-Raphson trajectory optimization-generator 1

Computer program constructs a sequence of optimal solutions to dynamically-approximate linear equations. Specification of the number and type of subarcs in the optimal solution allows simultaneous satisfaction of all switching criteria.

Cope, D. D.↗

Forward Stochastic Nonlinear Adaptive Control Method

New method of computation for optimal stochastic nonlinear and adaptive control undergoing development. Solves systematically stochastic dynamic programming equations forward in time, using nested-stochastic-approximation technique. Main advantage, simplicity of programming and reduced complexity with clear performance/computation trade-offs.

Bayard, David S.↗

Autonomous vehicle motion control, approximate maps, and fuzzy logic

Progress on research on the control of actions of autonomous mobile agents using fuzzy logic is presented. The innovations described encompass theoretical and applied developments. At the theoretical level, results of research leading to the combined utilization of conventional artificial planning techniques with fuzzy logic approaches for the control of local motion and perception actions are presented. Also formulations of dynamic programming approaches to optimal control in the context of the analysis of approximate models of the real world are examined. Also a new approach to goal conflict resolution that does not require specification of numerical values representing relative goal importance is reviewed. Applied developments include the introduction of the notion of approximate map. A fuzzy relational database structure for the representation of vague and imprecise information about the robot's environment is proposed. Also the central notions of control point and control structure are discussed.

Ruspini, Enrique H.↗

Implementation of an integrated op-amp based chaotic neuron model and observation of its chaotic dynamics

This paper presents a fully integrated circuit implementation of an operational amplifier (op-amp) based chaotic neuron model with a bipolar output function, experimental measurements, and analyses of its chaotic behavior. The proposed chaotic neuron model integrated circuit consists of several op-amps, sample and hold circuits, a nonlinear function block for chaotic signal generation, a clock generator, a nonlinear output function, etc. Based on the HSPICE (circuit program) simulation results, approximated empirical equations for analyses were formulated. Then, the chaotic dynamical responses such as bifurcation diagrams, time series, and Lyapunov exponent were calculated using these empirical equations. In addition, we performed simulations about two chaotic neuron systems with four synapses to confirm neural network connections and got normal behavior of the chaotic neuron such as internal state bifurcation diagram according to the synaptic weight variation. The proposed circuit was fabricated using a 0.8-{mu}m single poly complementary metal-oxide semiconductor technology. Measurements of the fabricated single chaotic neuron with {+-}2.5 V power supplies and a 10 kHz sampling clock frequency were carried out and compared with the simulated results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Robot path planning with distance-safety criterion

A method for determining an optimal path with a weighted distance-safety criterion is developed. The goal is to strike a compromise between the shortest path and the centerline path, which is safer. The method is composed of three parts: (i) construction of a region map by dividing the workspace, (ii) interregion optimization to determine the entry and departure points of the path in each region, and (iii) intraregion optimization for determining the (optimal) path segment within each region. The region map is generated by using an approximate Voronoi diagram, and region optimization is achieved using variational dynamic programming. Although developed for 2-D problems, the method can be easily extended to a class of 3-D problems. Numerical examples are presented to demonstrate the method.

Suh, Suk-Hwan↗

A parallel trajectory optimization tool for aerospace plane guidance

A parallel trajectory optimization algorithm is being developed. One possible mission is to provide real-time, on-line guidance for the National Aerospace Plane. The algorithm solves a discrete-time problem via the augmented Lagrangian nonlinear programming algorithm. The algorithm exploits the dynamic programming structure of the problem to achieve parallelism in calculating cost functions, gradients, constraints, Jacobians, Hessian approximations, search directions, and merit functions. Special additions to the augmented Lagrangian algorithm achieve robust convergence, achieve (almost) superlinear local convergence, and deal with constraint curvature efficiency. The algorithm can handle control and state inequality constraints such as angle-of-attack and dynamic pressure constraints. Portions of the algorithm have been tested. The nonlinear programming core algorithm performs well on a variety of static test problems and on an orbit transfer problem. The parallel search direction algorithm can reduce wall clock time by a factor of 10 for this part of the computation task.

Psiaki, Mark L.↗

A computational algorithm for spacecraft control and momentum management

Developments in the area of nonlinear control theory have shown how coordinate changes in the state and input spaces of a dynamical system can be used to transform certain nonlinear differential equations into equivalent linear equations. These techniques are applied to the control of a spacecraft equipped with momentum exchange devices. An optimal control problem is formulated that incorporates a nonlinear spacecraft model. An algorithm is developed for solving the optimization problem using feedback linearization to transform to an equivalent problem involving a linear dynamical constraint and a functional approximation technique to solve for the linear dynamics in terms of the control. The original problem is transformed into an unconstrained nonlinear quadratic program that yields an approximate solution to the original problem. Two examples are presented to illustrate the results.

Dzielski, John↗

Path Planning: Differential Dynamic Programming and Model Predictive Path Integral Control on VTOL Aircraft

This paper explores two optimal control approaches, widely used in robotics, to establish their viability as real-time trajectory planners for vehicle configurations envisioned for the emerging aviation sector of Urban Air Mobility (UAM). Differential Dynamic Programming (DDP) enables planning over highly nonlinear dynamics using second-order approximations along a nominal trajectory, and displays quadratic convergence to a local solution. Model Predictive Path Integral (MPPI) is a stochastic sampling-based algorithm that can optimize for general cost criteria, including potentially highly nonlinear formulations, and supports parallel computation through the use of modern GPU hardware. In this work, DDP and MPPI were implemented using model predictive control (MPC), and the results indicate they are able to successfully transition the aircraft over different flight envelopes and generate trajectories unique to UAM vehicles.

Differential Dynamic Programming↗

Computational alternatives to obtain time optimal jet engine control

Two computational methods to determine an open loop time optimal control sequence for a simple single spool turbojet engine are described by a set of nonlinear differential equations. Both methods are modifications of widely accepted algorithms which can solve fixed time unconstrained optimal control problems with a free right end. Constrained problems to be considered have fixed right ends and free time. Dynamic programming is defined on a standard problem and it yields a successive approximation solution to the time optimal problem of interest. A feedback control law is obtained and it is then used to determine the corresponding open loop control sequence. The Fletcher-Reeves conjugate gradient method has been selected for adaptation to solve a nonlinear optimal control problem with state variable and control constraints.

Basso, R. J.↗

Testing of DLR C/C-SiC for HIFiRE 8 Scramjet Combustor

Ceramic Matrix Composites (CMCs) have been proposed for hot structures in scramjet combustors. Previous studies have calculated significant weight savings by utilizing CMCs (active and passive) versus actively cooled metallic scramjet structures. Both a C/C and a C/C-SiC material system fabricated by DLR (Stuttgart, Germany) are being considered for use in a passively cooled combustor design for HIFiRE 8, a joint Australia / AFRL hypersonic flight program, expected to fly at Mach 7 for approximately 30 sec, at a dynamic pressure of 55 kPa. Flat panels of the DLR C/C and the C/C-SiC were tested in the NASA Langley Direct Connect Rig (DCR) at Mach 5 and Mach 6 enthalpy for several minutes. Gaseous hydrogen fuel was used to fuel the scramjet combustor. The test panels were instrumented with embedded Type K and Type S thermocouples. Zirconia felt insulation was used in some of the tests to increase the surface temperature of the C/C-SiC panel for approximately 350degF. The final C/C-SiC panel was tested for 3 cycles totaling over 135 sec at Mach 6 enthalpy. Slightly more erosion was observed on the C/C panel than the C/C-SiC panels, but both material systems demonstrated acceptable recession performance for the HIFiRE 8 flight.

Glass, David E.↗

Testing of DLR C/C-SiC and C/C for HIFiRE 8 Scramjet Combustor

Ceramic Matrix Composites (CMCs) have been proposed for use as lightweight hot structures in scramjet combustors. Previous studies have calculated significant weight savings by utilizing CMCs (active and passive) versus actively cooled metallic scramjet structures. Both a carbon/carbon (C/C) and a carbon/carbon-silicon carbide (C/C-SiC) material fabricated by DLR (Stuttgart, Germany) are being considered for use in a passively cooled combustor design for Hypersonic International Flight Research Experimentation (HIFiRE) 8, a joint Australia / Air Force Research Laboratory hypersonic flight program, expected to fly at Mach 7 for approximately 30 sec, at a dynamic pressure of 55 kilopascals. Flat panels of the DLR C/C and C/C-SiC materials were installed downstream of a hydrogen-fueled, dual-mode scramjet combustor and tested for several minutes at conditions simulating flight at Mach 5 and Mach 6. Gaseous hydrogen fuel was used to fuel the scramjet combustor. The test panels were instrumented with embedded Type K and Type S thermocouples. Zirconia felt insulation was used during some of the tests to reduce heat loss from the back surface and thus increase the heated surface temperature of the C/C-SiC panel approximately 177 C (350 F). The final C/C-SiC panel was tested for three cycles totaling over 135 sec at Mach 6 enthalpy. Slightly more erosion was observed on the C/C panel than the C/C-SiC panels, but both material systems demonstrated acceptable recession performance for the HIFiRE 8 flight.

Glass, David E.↗