A modified sweep method for control optimization
Solution of trajectory optimization problems by calculus of variations, dynamic programming, and Pontryagin's Principle
Colunga, D.↗
SEARCH · Engineering Papers
Results for “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.
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Study of non-linear optimization techniques
Nonlinear optimization techniques in dynamic programming and solution of ordinary nonlinear differential equations by Runge-Kutta method
Shanks, E. B.↗
Accelerated procedures for the solution of discret e Markov control problems
Accelerated procedures for Markov chain model optimal control problems solution with computation time advantage over usual dynamic programming
Kleinman, A. J.↗
An optimal stochastic control problem with observation cost
Linear system optimal stochastic control and observation strategies simultaneous determination with quadratic cost by dynamic programming
Cooper, C. A.↗
Optimal lateral guidance for low L/D shuttle vehicle entry
Optimal lateral guidance switching thresholds for low L/D shuttle vehicle entry, using optimal stochastic control theory for problem formulation in conjunction with dynamic programming
Deyst, J. J.↗
On stochastic control and optimal measurement strategies
The control of stochastic dynamic systems is studied with particular emphasis on those which influence the quality or nature of the measurements which are made to effect control. Four main areas are discussed: (1) the meaning of stochastic optimality and the means by which dynamic programming may be applied to solve a combined control/measurement problem; (2) a technique by which it is possible to apply deterministic methods, specifically the minimum principle, to the study of stochastic problems; (3) the methods described are applied to linear systems with Gaussian disturbances to study the structure of the resulting control system; and (4) several applications are considered.
Kramer, L. C.↗
The synthesis of optimal controls for linear, time-optimal problems with retarded controls.
Optimization problems involving linear systems with retardations in the controls are studied in a systematic way. Some physical motivation for the problems is discussed. The topics covered are: controllability, existence and uniqueness of the optimal control, sufficient conditions, techniques of synthesis, and dynamic programming. A number of solved examples are presented.
Banks, H. T.↗
Minimum-energy control of a class of electrically driven vehicles.
A minimum-energy controller is designed and built for a class of electrically driven vehicles according to the theoretical concepts determined by the application of modern control theory. Theoretical results are obtained by making several justifiable assumptions in the dynamical equations of the system and solving the resulting stochastic optimal control problem by Bellman's dynamic programming technique. Several practical and economical considerations are taken into account for the mechanization of the minimum-energy control law.
Sahinkaya, Y. E.↗
On the minimax feedback control of uncertain dynamic systems.
In this paper the problem of optimal feedback control of uncertain discrete-time dynamic systems is considered where the uncertain quantities do not have a stochastic description but instead are known to belong to given sets. The problem is converted to a sequential minimax problem and dynamic programming is suggested as a general method for its solution. The notion of a sufficiently informative function, which parallels the notion of a sufficient statistic of stochastic optimal control, is introduced, and conditions under which the optimal controller decomposes into an estimator and an actuator are identified.
Bertsekas, D. P.↗
Techniques for generating highly reliable redundant systems.
A simple heuristic algorithm for designing highly reliable modularly redundant computer systems under complexity constraints is presented. The technique, which produces near optimal solutions, is intuitively appealing and easy to apply. The algorithms performance is shown to compare very well with the optimal solution obtained via a computerized model for dynamic programming.
White, J. B.↗
A summary report on system effectiveness and optimization study
Report treats optimization and effectiveness separately. Report illustrates example of dynamic programming solution to system optimization. Computer algorithm has been developed to solve effectiveness problem and is included in report.
Williamson, O. L.↗
A global station coordinate solution based upon camera and laser data - GSFC 1973
Results for the geocentric coordinates of 72 globally distributed satellite tracking stations consisting of 58 cameras and 14 lasers are presented. The observational data for this solution consists of over 65,000 optical observations and more than 350 laser passes recorded during the National Geodetic Satellite Program, the 1968 Centre National d'Etudes Spatiales/Smithsonian Astrophysical Observatory (SAO) Program, and International Satellite Geodesy Experiment Program. Dynamic methods were used. The data were analyzed with the GSFC GEM and SAO 1969 Standard Earth Gravity Models. The recent value of GM = 398600.8 cu km/sec square derived at the Jet Propulsion Laboratory (JPL) gave the best results for this combination laser/optical solution. Solutions are made with the deep space solution of JPL (LS-25 solution) including results obtained at GSFC from Mariner-9 Unified B-Band tracking. Datum transformation parameters relating North America, Europe, South America, and Australia are given, enabling the positions of some 200 other tracking stations to be placed in the geocentric system.
Marsh, J. G.↗
Sufficiently informative functions and the minimax feedback control of uncertain dynamic systems.
The problem of optimal feedback control of uncertain discrete-time dynamic systems is considered where the uncertain quantities do not have a stochastic description but instead are known to belong to given sets. The problem is converted to a sequential minimax problem and dynamic programming is suggested as a general method for its solution. The notion of a sufficiently informative function, which parallels the notion of a sufficient statistic of stochastic optimal control, is introduced, and conditions under which the optimal controller decomposes into an estimator and an actuator are identified.
Bertsekas, D. P.↗
Solution of the stochastic control problem in unbounded domains.
Bellman's dynamic programming equation for the optimal index and control law for stochastic control problems is a parabolic or elliptic partial differential equation frequently defined in an unbounded domain. Existing methods of solution require bounded domain approximations, the application of singular perturbation techniques or Monte Carlo simulation procedures. In this paper, using the fact that Poisson impulse noise tends to a Gaussian process under certain limiting conditions, a method which achieves an arbitrarily good approximate solution to the stochastic control problem is given. The method uses the two iterative techniques of successive approximation and quasi-linearization and is inherently more efficient than existing methods of solution.
Robinson, P.↗
Analysis and compensation of an aircraft simulator control loading system with compliant linkage
A hydraulic control loading system for aircraft simulation was analyzed to find the causes of undesirable low frequency oscillations and loading effects in the output. The hypothesis of mechanical compliance in the control linkage was substantiated by comparing the behavior of a mathematical model of the system with previously obtained experimental data. A compensation scheme based on the minimum integral of the squared difference between desired and actual output was shown to be effective in reducing the undesirable output effects. The structure of the proposed compensation was computed by use of a dynamic programing algorithm and a linear state space model of the fixed elements in the system.
Johnson, P. R.↗
A new methodology to integrate planetary quarantine requirements into mission planning, with application to a Jupiter orbiter
A new methodology is proposed for integrating planetary quarantine objectives into space exploration planning. This methodology is designed to remedy the major weaknesses inherent in the current formulation of planetary quarantine requirements. Application of the methodology is illustrated by a tutorial analysis of a proposed Jupiter Orbiter mission. The proposed methodology reformulates planetary quarantine planning as a sequential decision problem. Rather than concentrating on a nominal plan, all decision alternatives and possible consequences are laid out in a decision tree. Probabilities and values are associated with the outcomes, including the outcome of contamination. The process of allocating probabilities, which could not be made perfectly unambiguous and systematic, is replaced by decomposition and optimization techniques based on principles of dynamic programming. Thus, the new methodology provides logical integration of all available information and allows selection of the best strategy consistent with quarantine and other space exploration goals.
Howard, R. A.↗
Goddard laser systems and their accuracies
The latest Goddard laser systems, and their use in the Earth Dynamic Program are described. The tracking accuracies obtained using actual field data are discussed.
Vonbun, F. O.↗
On optimal control of linear systems in the presence of multiplicative noise
This correspondence considers the problem of optimal regulator design for discrete time linear systems subjected to white state-dependent and control-dependent noise in addition to additive white noise in the input and the observations. A pseudo-deterministic problem is first defined in which multiplicative and additive input disturbances are present, but noise-free measurements of the complete state vector are available. This problem is solved via discrete dynamic programming. Next is formulated the problem in which the number of measurements is less than that of the state variables and the measurements are contaminated with state-dependent noise. The inseparability of control and estimation is brought into focus, and an 'enforced separation' solution is obtained via heuristic reasoning in which the control gains are shown to be the same as those in the pseudo-deterministic problem. An optimal linear state estimator is given in order to implement the controller.
Joshi, S. M.↗