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Auslander, D. M.

Publications and source records attributed to Auslander, D. M..

Dynamic Considerations for Control of Closed Life Support Systems

Reliability of closed life support systems depend on their ability to continue supplying the crew's needs during perturbations and equipment failures. The dynamic considerations interact with the basic static design through the sizing of storages, the specification of excess capacities in processors, and the choice of system initial state. A very simple system flow model was used to examine the possibilities for system failures even when there is sufficient storage to buffer the immediate effects of the perturbation. Two control schemes are shown which have different dynamic consequences in response to component failures.

Babcock, P. S.

Control and modeling of a CELSS (Controlled Ecological Life Support System)

Research topics that arise from the conceptualization of control for closed life support systems which are life support systems in which all or most of the mass is recycled are discussed. Modeling and control of uncertain and poorly defined systems, resource allocation in closed life support systems, and control structures or systems with delay and closure are emphasized.

Auslander, D. M.

Design of nonlinear discrete-time controllers using a parameter space sampling procedure

The design of nonlinear discrete-time controllers is investigated where the control algorithm assumes a special form. State-dependent control actions are obtained from tables whose values are the design parameters. A new design methodology capable of dealing with nonlinear systems containing parameter uncertainty is used to obtain the controller design. Various controller strategies are presented and illustrated through an example.

Young, G. E.

A design methodology for nonlinear systems containing parameter uncertainty

In the present design methodology for nonlinear systems containing parameter uncertainty, a generalized sensitivity analysis is incorporated which employs parameter space sampling and statistical inference. For the case of a system with j adjustable and k nonadjustable parameters, this methodology (which includes an adaptive random search strategy) is used to determine the combination of j adjustable parameter values which maximize the probability of those performance indices which simultaneously satisfy design criteria in spite of the uncertainty due to k nonadjustable parameters.

Young, G. E.

CELSS System Control Overview

A CELSS presents unique control problems at all levels. The question of how much control is necessary (as opposed to just useful) is addressed. On the largest scale, that of overall system control, this reduces to the question, ""Is a CELSS that has been designed for steady-state balance in all its flows, with the addition of reasonable amounts of buffering, stable in the face of perturbations from that operating point?'' That is, if some inadvertent perturbation occurs (temporary shutdown of some component, for example), will the system return to its original operating point without the imposition of a global control scheme? If the system is stable in that sense, any kind of large-scale control scheme will be useful for optimizing the system, but will not be necessary.

Auslander, D. M.

Application of control theory to dynamic systems simulation

The application of control theory is applied to dynamic systems simulation. Theory and methodology applicable to controlled ecological life support systems are considered. Spatial effects on system stability, design of control systems with uncertain parameters, and an interactive computing language (PARASOL-II) designed for dynamic system simulation, report quality graphics, data acquisition, and simple real time control are discussed.

Auslander, D. M.

A simulation-based approach to the design of control systems with uncertain parameters

A design method for control systems with uncertain parameters is presented. The method utilizes a generalized sensitivity approach which separates the parameter space into regions which produce a system response that satisfies given design criteria and regions which do not. Nonparametric statistics and confidence limits for the binomial distribution are used to determine degree of parameter sensitivity and to locate regions in the parameter space which maximize the probability of producing a desirable system response. In an example it is shown that a given parameter may have to be known to a lesser degree of uncertainty to be able to specify a satisfactory design.

Auslander, D. M.

Design of control systems with uncertain parameters

A design method for control systems with uncertain parameters is presented. The method utilizes a generalized sensitivity approach which separates the parameter space into regions which produce a system response that satisfies given design criteria and regions which do not. Nonparametric statistics and confidence limits for the binomial distribution are used to determine degree of parameter sensitivity and to locate regions in the parameter space which maximize the probability of producing a desirable system response. In an example it is shown that a given parameter may have to be known to a lesser degree of uncertainty to be able to specify a satisfactory design.

Auslander, D. M.