Theory of optimum discrete time systems.
Maximum principle in optimization of discrete time systems described by difference equations
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Maximum principle in optimization of discrete time systems described by difference equations
Pontryagin maximum principle applied to solution of optimal control problems by hybrid computer, using digital parameter optimizer to solve two- point boundary value problem
Chapter 1 briefly reviews several related topics associated with the symmetrization of systems of conservation laws and quasi-conservation laws: (1) Basic Entropy Symmetrization Theory; (2) Symmetrization and eigenvector scaling; (3) Symmetrization of the compressible Navier-Stokes equations; and (4) Symmetrization of the quasi-conservative form of the magnetohydrodynamic (MHD) equations. Chapter 2 describes one of the best known tools employed in the study of differential equations, the maximum principle: any function f(x) which satisfies the inequality f(double prime)>0 on the interval [a,b] attains its maximum value at one of the endpoints on the interval. Chapter three examines the upwind finite volume schemes for scalar and system conservation laws. The basic tasks in the upwind finite volume approach have already been presented: reconstruction, flux evaluation, and evolution. By far, the most difficult task in this process is the reconstruction step.
Equations are derived for maximizing range for specified initial and final values of mass and altitude. Constant-velocity flight is assumed, and normal acceleration is neglected. The problem is solved by using the maximum principle. Optimal trajectories are obtained and uniqueness is demonstrated. Results are obtained for a supersonic airplane. Curves are presented which can be used to obtain the optimal trajectory and maximum range for a range of initial and final mass and altitude. The optimal range is compared to the range obtained by using the standard cruise trajectory profile (consisting of a Bereguet cruise plus maximum- and minimum-thrust connecting segments) and to the range obtained at constant-altitude cruise.
Equations are derived by using branched trajectory optimization techniques and the maximum principle to maximize the payload capability of a reusable tug/expendable kickstage vehicle configuration for planetary missions. The two stages and the payload are launched into a low earth orbit by a single space shuttle. The analysis includes correction for precession of the orbit. This correction is done by the tug. The tug propels the payload and the kickstage to an energy beyond earth escape and returns within a specified time to the precessed orbit. After separating from the tug, the kickstage accelerates the payload to the required injection conditions. Planetary injection conditions are specified by the mission energy and a fixed declination and right ascension of the outgoing asymptote. The multipoint boundary value problem resulting from the analysis is solved by a Newton-Raphson iteration technique. Partial derivatives of the boundary conditions are obtained by perturbing the initial conditions one at a time, integrating the trajectory and adjoint equations, and observing the changes in boundary conditions. Maximum payload capability is derived for two typical mission energies. In addition, the variations of several mission and stage parameters are also examined.
Pontryagin maximum principle to optimize attitude control systems on the basis of minimum fuel or energy consumption
Deterministic optimal control, discussing Bellman dynamic programming method, Pontryagin maximum principle, orbital transfer, interplanetary guidance, etc
Iterative solution of time optimal control boundary value problem resulting from application of Pontryagin maximum principle
Determining optimum atmospheric reentry trajectories using Pontryagin maximum principle
Deterministic optimal control, discussing Bellman dynamic programming method, Pontryagin maximum principle, orbital transfer, interplanetary guidance, etc
Variational problems involving functional differential equations, and derivation of general maximum principle involving adjoint variables or multipliers
Pontryagin maximum principle, calculus of variations, and dynamic programming optimization techniques applied to trajectory and guidance problems
Relation between optimal control problem and Liapunov functions, and calculus of variations and maximum principle methods of solving synthesis problems
Optimal control of linear process with bounded control amplitude and rates using maximum principle
Pontryagin maximum principle used to study stability of periodic equations in time optimal control problems
Production scheduling optimization by using discrete form of Pontryagin maximum principle
Optimal control in Banach spaces, deriving maximum principle for cost functional
Adaptive random search algorithm utilizing boundary cost-function hypersurfaces measurement to implement Pontryagin maximum principle, discussing hybrid computer use, iterative solution and convergence properties