A control theoretic approach to manned-vehicle systems analysis

Kleinman, David L.; Baron, Sheldon; Levison, William H.

doi:10.1109/tac.1971.1099842

Cited by 181 publications

(66 citation statements)

References 7 publications

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“…In the field of control engineering, through the 1950s and 1960s a large body of work was produced on the behavior of pilots as surveyed in [14]. The most relevant work from this field is [15], [16], clarified by [17], which proposes an LQG model of pilot response. This is similar to the current paper in that human behavior was compared to that of a controller design based on LQG.…”

Section: A Assumptions Control Theory Background and Past Workmentioning

confidence: 99%

Visuomotor Optimality and its Utility in Parametrization of Response

Sherback

D’Andrea²

2008

IEEE Trans. Biomed. Eng.

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Abstract-We present a method of characterizing visuomotor response by inferring subject-specific physiologically meaningful parameters within the framework of optimal control theory. The characterization of visuomotor response is of interest in the assessment of impairment and rehabilitation, the analysis of man-machine systems, and sensorimotor research. We model visuomotor response as a Linear Quadratic Gaussian (LQG) controller, a Bayesian optimal state estimator in series with a linear quadratic regulator. Subjects used a modified computer mouse to attempt to keep a displayed cursor at a fixed desired location despite a Gaussian random disturbance and simple cursor dynamics. Nearly all subjects' behavior was consistent with the hypothesized optimality. Experimental data was used to fit an LQG model whose assumptions are simple and consistent with other sensorimotor work. The parametrization is parsimonious and yields quantities of clear physiological meaning: noise intensity, level of exertion, delay, and noise bandwidth. Inferred control cost and noise intensity varied significantly across subjects. Response variations were consistent with changes in exerted effort. This is a novel example of the role of optimal control theory in explaining variance in human visuomotor response. We also present technical improvements on the use of LQG in human operator modeling.

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Section: A Assumptions Control Theory Background and Past Workmentioning

confidence: 99%

Visuomotor Optimality and its Utility in Parametrization of Response

Sherback

D’Andrea²

2008

IEEE Trans. Biomed. Eng.

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show abstract

“…Past experience has revealed a fair degree of orthogonality among the various model parameters. For example, we have found that the values of noise-related parameters which provide the best match to the measured remnant spectrum are relatively independent of the choice of time-delay and "motor-lag" parameters (Kleinman, Baron and Levison, 1971). This circumstance simplifies the matching procedure and allows us to differentiate among ehe various ways in which the pilot's performance capability cim be affected.…”

Section: 2 Model-matching Techniquesmentioning

confidence: 94%

Tactile Display for Aircraft Control

Ross¹,

Sanneman²,

Levison³

et al. 1973

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“…This shows the existence of proper observer gain k in Equation (8). Actually, the value of observer gain k is determined by a curve-fitting identification program.…”

Section: Securit T\lassification Of This Page(fhon Data Entered)mentioning

confidence: 95%