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At least 289 records · Page 16

Optimal control of sun tracking solar concentrators

Application of the modern control theory to derive an optimal sun tracking control for a point focusing solar concentrator is presented. A standard tracking problem converted to regulator problem using a sun rate input achieves an almost zero steady state tracking error with the optimal control formulation. However, these control techniques are costly because optimal type algorithms require large computing systems, thus they will be used mainly as comparison standards for other types of control algorithms and help in their development.

Hughes, R. O.↗

Development of an hp-version finite element method for computational optimal control

The purpose of this research effort is to develop a means to use, and to ultimately implement, hp-version finite elements in the numerical solution of optimal control problems. The hybrid MACSYMA/FORTRAN code GENCODE was developed which utilized h-version finite elements to successfully approximate solutions to a wide class of optimal control problems. In that code the means for improvement of the solution was the refinement of the time-discretization mesh. With the extension to hp-version finite elements, the degrees of freedom include both nodal values and extra interior values associated with the unknown states, co-states, and controls, the number of which depends on the order of the shape functions in each element.

Hodges, Dewey H.↗

Extremum seeking for optimal control problems with unknown time-varying systems and unknown objective functions

We consider the problem of optimal feedback control of an unknown, noisy, time-varying, dynamic system that is initialized repeatedly. Examples include a robotic manipulator which must perform the same motion, such as assisting a human, repeatedly and accelerating cavities in particle accelerators which are turned on for a fraction of a second with given initial conditions and vary slowly due to temperature fluctuations. In this paper, we present an approach that applies to systems of practical interest. The method presented here is model independent; does not require knowledge of the objective function; is robust to measurement noise; is applicable for any set of initial conditions; is applicable to simultaneously controlling an arbitrary number of parameters; and may be implemented with a broad range of continuous or discontinuous functions such as sine or square waves. For systems with convex cost functions we prove that our algorithm will produce controllers that approach the minimal cost. For linear systems we reproduce the cost minimizing linear quadratic regulator optimal controller that could have been designed analytically had the system and cost function been known. We demonstrate the effectiveness of the algorithm with simulation studies of noisy and time-varying systems.

42 ENGINEERING↗

Optimal Control Surface Layout for an Aeroservoelastic Wingbox

This paper demonstrates a technique for locating the optimal control surface layout of an aeroservoelastic Common Research Model wingbox, in the context of maneuver load alleviation and active utter suppression. The combinatorial actuator layout design is solved using ideas borrowed from topology optimization, where the effectiveness of a given control surface is tied to a layout design variable, which varies from zero (the actuator is removed) to one (the actuator is retained). These layout design variables are optimized concurrently with a large number of structural wingbox sizing variables and control surface actuation variables, in order to minimize the sum of structural weight and actuator weight. Results are presented that demonstrate interdependencies between structural sizing patterns and optimal control surface layouts, for both static and dynamic aeroelastic physics.

Stanford, Bret K.↗

Application of optimal control theory to the design of the NASA/JPL 70-meter antenna servos

The application of Linear Quadratic Gaussian (LQG) techniques to the design of the 70-m axis servos is described. Linear quadratic optimal control and Kalman filter theory are reviewed, and model development and verification are discussed. Families of optimal controller and Kalman filter gain vectors were generated by varying weight parameters. Performance specifications were used to select final gain vectors.

Alvarez, L. S.↗

A Nonlinear Physics-Based Optimal Control Method for Magnetostrictive Actuators

This paper addresses the development of a nonlinear optimal control methodology for magnetostrictive actuators. At moderate to high drive levels, the output from these actuators is highly nonlinear and contains significant magnetic and magnetomechanical hysteresis. These dynamics must be accommodated by models and control laws to utilize the full capabilities of the actuators. A characterization based upon ferromagnetic mean field theory provides a model which accurately quantifies both transient and steady state actuator dynamics under a variety of operating conditions. The control method consists of a linear perturbation feedback law used in combination with an optimal open loop nonlinear control. The nonlinear control incorporates the hysteresis and nonlinearities inherent to the transducer and can be computed offline. The feedback control is constructed through linearization of the perturbed system about the optimal system and is efficient for online implementation. As demonstrated through numerical examples, the combined hybrid control is robust and can be readily implemented in linear PDE-based structural models.

Smith, Ralph C.↗

A dual method for optimal control problems with initial and final boundary constraints.

This paper presents two new algorithms belonging to the family of dual methods of centers. The first can be used for solving fixed time optimal control problems with inequality constraints on the initial and terminal states. The second one can be used for solving fixed time optimal control problems with inequality constraints on the initial and terminal states and with affine instantaneous inequality constraints on the control. Convergence is established for both algorithms. Qualitative reasoning indicates that the rate of convergence is linear.

Pironneau, O.↗

Using Markov Models of Fault Growth Physics and Environmental Stresses to Optimize Control Actions

A generalized Markov chain representation of fault dynamics is presented for the case that available modeling of fault growth physics and future environmental stresses can be represented by two independent stochastic process models. A contrived but representatively challenging example will be presented and analyzed, in which uncertainty in the modeling of fault growth physics is represented by a uniformly distributed dice throwing process, and a discrete random walk is used to represent uncertain modeling of future exogenous loading demands to be placed on the system. A finite horizon dynamic programming algorithm is used to solve for an optimal control policy over a finite time window for the case that stochastic models representing physics of failure and future environmental stresses are known, and the states of both stochastic processes are observable by implemented control routines. The fundamental limitations of optimization performed in the presence of uncertain modeling information are examined by comparing the outcomes obtained from simulations of an optimizing control policy with the outcomes that would be achievable if all modeling uncertainties were removed from the system.

Bole, Brian↗

The optimal control of merging aircraft-derivation of the hybrid air traffic controller.

The Federal Aviation Administration has initiated a program to automate its existing manual air traffic handling procedures. One procedure, whose automation is expected to increase controller efficiency by 2.6 to 2.9 times, is known as aircraft merging. This procedure is concerned with the merging of N aircraft, which are distributed among K feeder routes, into one or more final routes. The question of obtaining an exactly realizable and easily implementable automatic controller for merging is discussed. The optimal control of a linear system with state and control constraints is considered.

Schatz, J. G.↗

Constrained optimal controller for linear systems with state and control dependent disturbance

The problem is posed with the additional constraints that the dynamic controller uses only noise-corrupted outputs, and that its dimension is significantly lower than that of a Kalman filter. The unknown disturbance is viewed as an adversary which tries to maximize a performance criterion: a criterion that the controller gains attempt to minimize. The optimal controller gains are determined by solving a nonlinear matrix two-point boundary value problem.

Basuthakur, S.↗

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.↗

Optimal Control Design using an H(sub 2) Method for the Glovebox Integrated Microgravity Isolation Technology (G-Limit)

The acceleration environment on the International Space Station (ISS) will likely exceed the requirements of many micro-gravity experiments. The Glovebox Integrated Microgravity Isolation Technology (g-LIMIT) is being built by the NASA Marshall Space Flight Center to attenuate the nominal acceleration environment and provide some isolation for microgravity science experiments. G-LIMIT uses Lorentz (voice-coil) magnetic actuators to isolate a platform for mounting science payloads from the nominal acceleration environment. The system utilizes payload acceleration, relative position, and relative orientation measurements in a feedback controller to accomplish the vibration isolation task. The controller provides current commands to six magnetic actuators, producing the required experiment isolation from the ISS acceleration environment. This paper presents the development of a candidate control law to meet the acceleration attenuation requirements for the g-LIMIT experiment platform. The controller design is developed using linear optimal control techniques for frequency-weighted H(sub 2) norms. Comparison of the performance and robustness to plant uncertainty for this control design approach is included in the discussion.

Calhoun, Philip C.↗