Results 221 to 230 of about 281,884 (245)

Modeling of Uncertain Systems

2013
As discussed in Chap. 1 it is well understood that uncertainties are unavoidable in a real control system. The uncertainty can be classified into two categories: disturbance signals and dynamic perturbations. The former includes input and output disturbance (such as a gust on an aircraft), sensor noise and actuator noise, etc. The latter represents the
Da-Wei Gu, Petko H. Petkov, Mihail M. Konstantinov   +2 more
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Control of Uncertain Systems

2009
Novel direct adaptive robust state and output feedback controllers are presented for the output tracking control of a class of nonlinear systems with unknown system dynamics and disturbances. Both controllers employ a variable-structure radial basis function (RBF) network that can determine its structure dynamically to approximate unknown system ...
Jianming Lian, Stanislaw H. Żak
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Compensability of uncertain systems

29th IEEE Conference on Decision and Control, 1990
The uncertainty of linear discrete-time systems with white stochastic parameters is considered in relation with the properties of mean-square stability and the ability to provide compensation. A measure for the uncertainty in the system matrices is introduced.
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The Uncertain Nervous System.

Archives of Neurology, 1969
This well-written book by the Head of the Division of Physiology and Pharmacology of the (British) National Institutes of Medical Research examines the current status and explores possible future trends of the study of the central nervous system as brain.
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Estimation of Uncertain Systems

1973
Publisher Summary This chapter describes the state estimation problem with parameter uncertainties. The Kalman-Bucy filter gives the unbiased, minimum variance estimate of the state vector of a linear dynamic system that is disturbed by additive white noise when measurements of the state vector are linear, but disturbed by white noise.
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Uncertain Systems

2000
Geir E. Dullerud, Fernando Paganini
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Introduction to Uncertain Systems

2004
Uncertainty is one of the main features of complex and intelligent decision making systems. Various approaches, methods and techniques in this field have been developed for several decades, starting with such concepts and tools as adaptation, stochastic optimization and statistical decision theory (see e.g. [2, 3, 68, 79, 80]). The first period of this
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Uncertain Sampled-data Systems

1996
In this chapter we introduce the general sampled-data system configuration considered in this work. The system arrangement is shown in Figure 3.1. The figure shows a continuous time system G in feedback with a discrete time controller Kd through the sample and hold devices defined in (2.2). Also in feedback with G is the block diagonal system diag(Δ1,..
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Uncertain Systems

2005
Diederich Hinrichsen, Anthony J. Pritchard   +1 more
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Uncertain Systems and Robustness

2013
The ability of dealing with uncertainty (uncertain system) is an essential part when designing a robust feedback controller. The objective is indeed to determine the controller parameters ensuring acceptable performance of the closed-loop system despite the unknown disturbances affecting the system as well as the uncertainties about the plant dynamics.
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