J
John B. Moore
Researcher at Australian National University
Publications - 352
Citations - 19139
John B. Moore is an academic researcher from Australian National University. The author has contributed to research in topics: Adaptive control & Linear-quadratic-Gaussian control. The author has an hindex of 50, co-authored 352 publications receiving 18573 citations. Previous affiliations of John B. Moore include Akita University & University of Hong Kong.
Papers
More filters
Journal ArticleDOI
Least squares pole assignment by memoryless output feedback
Danchi Jiang,John B. Moore +1 more
TL;DR: In this article, a pole assignment problem for a linear time-invariant control system by memoryless output feedback is posed as a least squares optimisation problem and analyzed, and the cost functions are appropriately modified so as to obtain convergence of the corresponding gradient flow and existence of the global minimum.
Proceedings ArticleDOI
An instrumental variable approach for identification of hidden Markov models
Jeremy S. Thorne,John B. Moore +1 more
TL;DR: This instrumental variable method proposed offers the possibility of improved parameter estimation when the state of the HMM is correlated with the system noise.
Journal ArticleDOI
Tolerance of nonlinearities in time-varying optimal systems
TL;DR: Nominally linear optimal-control regulating systems are examined and it is found that a large degree of nonlinearity will not disturb the stability of the system.
Journal ArticleDOI
Brief paper: Recursive prediction error algorithms without a stability test
Haim Weiss,John B. Moore +1 more
TL;DR: Recursion prediction error identification schemes are studied which incorporate Kalman gain calculations to ensure exponential stability of the predictor and related recursions and the resulting algorithms are attractive for a wide range of applications.
Proceedings ArticleDOI
Adaptive disturbance rejection
TL;DR: In this paper, a direct adaptive algorithm applied to a linear plant is analyzed using averaging analysis, where the prior knowledge includes a nominal model and a stabilizing controller for the plant.