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Optimal control: linear quadratic methods
This augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems. It explores linear optimal control theory…
Hidden Markov Models: Estimation and Control
This paper presents a meta-modelling procedure called Markov Model Processing that automates the very labor-intensive and therefore time-heavy and therefore expensive process of HMMEstimation.
Linear Optimal Control
This book helps to fill the void in the market and does that in a superb manner by covering the standard topics such as Kalman filtering, innovations processes, smoothing, and adaptive and nonlinear estimation.
High Performance Control
Performance enhancement stabilizing controllers design environment off-line controller design iterated and nested (S, Q) design direct adaptive-Q control indirect (S, Q) adaptive control adaptive-Q…
Detectability and Stabilizability of Time-Varying Discrete-Time Linear Systems
The concepts of detectability and stabilizability are explored for time-varying systems. We study duality, invariance under feedback, an extended version of the lemma of Lyapunov, existence of…
Dextrous hand grasping force optimization
The task of grasping force optimization is formulated as an optimization problem on the smooth manifold of linearly constrained positive definite matrices for which there are known globally exponentially convergent solutions via gradient flows.
On-line estimation of hidden Markov model parameters based on the Kullback-Leibler information measure
The online EM schemes have significantly reduced memory requirements and improved convergence, and they can estimate HMM parameters that vary slowly with time or undergo infrequent jump changes.
Direct Kalman filtering approach for GPS/INS integration
We present a novel Kalman filtering approach for GPS/INS integration. In the approach, GPS and INS nonlinearities are preprocessed prior to a Kalman filter. The GPS preprocessed data are taken as…