1,721,292 research outputs found
Continuous-time Gauss-Markov processes with fixed reciprocal dynamics
No full textContinuing the work started in [11], in this paper we examine
the construction of Gauss-Markov processes with xed reciprocal
dynamics. We show how to construct Gauss-Markov processes, de-
ned on a nite interval, having xed initial and end-point densities
and belonging to a given reciprocal class. The problem of changing
the end-point density of a Markov process, while remaining in the
same reciprocal class, is also considered. A stochastic interpretation
of the results in terms of an optimal control problem is given
An application of Selective Modal Analysis to tokamak modeling and control
No full textIn this paper, the problem of model order reduction for tokamak devices is considered. Due to the complexity of the machine, the available models of the plasma behavior and its electromagnetic coupling with the active and metallic structures have to be very detailed to be usefully employed for simulation and control design. Such a level of detail consequently yields linearized models of the system of very high order. Having to deal with such high-order models makes the use of many control schemes quite complicated. To cope with this problem, the natural strategy is to derive models of reduced order, which reproduce with sufficient accuracy the full-order model behavior. The use of a reduction scheme which is based on selective modal analysis (SMA) is proposed. Its basic property is that the physical meaning of the state variables is preserved in the reduced model. This fact can be usefully employed both in the analysis of the system properties and for control design. In particular, the design of an LQG controller for the International Thermonuclear Experimental Reactor is discusse
Discrete-time LQG optimal control with actuator noise intensity related to actuator signal variance
No full textIn the paper the optimal LQG state feedback control of multivariable discrete-time systems with actuator noise related to the variance of the actuator signals is considered. The problem is solved for the finite-horizon case exploiting a matrix version of the maximum principle. The optimal feedback is given in terms of the solution of a generalized Riccati difference equatio
On the relative entropy of discrete-time Markov processes with given end-point densities
No full textGiven a Markov process x(k) defined over a finite interval I=[0,N], I⊂Z we construct a process x*(k) with the same initial density as x, but a different end-point density, which minimizes the relative entropy of x and x*. It is shown that x* is a Markov process in the same reciprocal class as x. In the Gaussian case, the minimum relative entropy problem is related to a minimum energy LQG optimal control proble
On the relative entropy of discrete-time Gauss-Markov processes with given end-point variances
No full text
A robust fault detection algorithm for the improvement of OTDR sensitivity
No full textIn the paper, an algorithm is presented for the detection of jump discontinuities in exponential signals buried in high level additive noise. It is employed as a post-processor in an optical time domain reflectometer (OTDR) to locate the position of discontinuities along the fiber. The proposed technique is based on a generalized likelihood ratio test applied to the innovation sequence resulting from Kalman filtering. A rigorous and thorough statistical analysis of the algorithm is reported, showing the achievable resolution together with the probability of error in the detection of fault
Designing and teaching of an effective engineering continuing education course: Modeling and simulation of HVAC systems
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