Abstract: The digital control system of mobile robots (MR) control is considered. It is shown that sequential interpretation of control algorithm operators, unfolding in physical time, suggests the occurrence of time delays between inputting data from sensors and outputting data to actuators. Another destabilizing control factor is presence of backlash in the joints of an actuator with an executive unit. Complex model of control system, which takes into account the dynamics of the MR, the dynamics of the digital controller and backlash in actuators, is worked out. The digital controller model is divided into two parts: the first part describes the control law embedded in the controller in the form of a control program that realizes a polling procedure when organizing transactions to sensors and actuators. The second part of the model describes the time delays that occur in the Von Neumann-type controller when processing data. To estimate time intervals, the algorithm is represented in the form of an ergodic semi-Markov process. For an ergodic semi-Markov process of common form, a method is proposed for estimation a wandering time from one arbitrary state to another arbitrary state. Example shows how the backlash and time delays affect the quality characteristics of the MR control system functioning.
Abstract: The driven processes of Wiener and Lévy are known
self-standing Gaussian-Markov processes for fitting non-linear
dynamical Vasciek model. In this paper, a coincidental Gaussian
density stationarity condition and autocorrelation function of the
two driven processes were established. This led to the conflation
of Wiener and Lévy processes so as to investigate the efficiency
of estimates incorporated into the one-dimensional Vasciek model
that was estimated via the Maximum Likelihood (ML) technique.
The conditional laws of drift, diffusion and stationarity process
was ascertained for the individual Wiener and Lévy processes as
well as the commingle of the two processes for a fixed effect
and Autoregressive like Vasciek model when subjected to financial
series; exchange rate of Naira-CFA Franc. In addition, the model
performance error of the sub-merged driven process was miniature
compared to the self-standing driven process of Wiener and Lévy.
Abstract: The paper describes the availability analysis of milling system of a rice milling plant using probabilistic approach. The subsystems under study are special purpose machines. The availability analysis of the system is carried out to determine the effect of failure and repair rates of each subsystem on overall performance (i.e. steady state availability) of system concerned. Further, on the basis of effect of repair rates on the system availability, maintenance repair priorities have been suggested. The problem is formulated using Markov Birth-Death process taking exponential distribution for probable failures and repair rates. The first order differential equations associated with transition diagram are developed by using mnemonic rule. These equations are solved using normalizing conditions and recursive method to drive out the steady state availability expression of the system. The findings of the paper are presented and discussed with the plant personnel to adopt a suitable maintenance policy to increase the productivity of the rice milling plant.
Abstract: In this paper, the potential use of an exponential
hidden Markov model to model a hidden pavement deterioration
process, i.e. one that is not directly measurable, is investigated. It is
assumed that the evolution of the physical condition, which is the
hidden process, and the evolution of the values of pavement distress
indicators, can be adequately described using discrete condition states
and modeled as a Markov processes. It is also assumed that condition
data can be collected by visual inspections over time and represented
continuously using an exponential distribution. The advantage of
using such a model in decision making process is illustrated through
an empirical study using real world data.
Abstract: In this paper we present a statistical analysis of Voice
over IP (VoIP) packet streams produced by the G.711 voice coder
with voice activity detection (VAD). During telephone conversation,
depending whether the interlocutor speaks (ON) or remains silent
(OFF), packets are produced or not by a voice coder. As index of
dispersion for both ON and OFF times distribution was greater than
one, we used hyperexponential distribution for approximation of
streams duration. For each stage of the hyperexponential distribution,
we tested goodness of our fits using graphical methods, we calculated
estimation errors, and performed Kolmogorov-Smirnov test.
Obtained results showed that the precise VoIP source model can be
based on the five-state Markov process.
Abstract: This paper discusses the performance modeling and availability analysis of Yarn Dyeing System of a Textile Industry. The Textile Industry is a complex and repairable engineering system. Yarn Dyeing System of Textile Industry consists of five subsystems arranged in series configuration. For performance modeling and analysis of availability, a performance evaluating model has been developed with the help of mathematical formulation based on Markov-Birth-Death Process. The differential equations have been developed on the basis of Probabilistic Approach using a Transition Diagram. These equations have further been solved using normalizing condition in order to develop the steady state availability, a performance measure of the system concerned. The system performance has been further analyzed with the help of decision matrices. These matrices provide various availability levels for different combinations of failure and repair rates for various subsystems. The findings of this paper are therefore, considered to be useful for the analysis of availability and determination of the best possible maintenance strategies which can be implemented in future to enhance the system performance.
Abstract: In this paper, we propose a single sample path based
algorithm with state aggregation to optimize the average rewards of
singularly perturbed Markov reward processes (SPMRPs) with a
large scale state spaces. It is assumed that such a reward process
depend on a set of parameters. Differing from the other kinds of
Markov chain, SPMRPs have their own hierarchical structure. Based
on this special structure, our algorithm can alleviate the load in the
optimization for performance. Moreover, our method can be applied
on line because of its evolution with the sample path simulated.
Compared with the original algorithm applied on these problems of
general MRPs, a new gradient formula for average reward
performance metric in SPMRPs is brought in, which will be proved
in Appendix, and then based on these gradients, the schedule of the
iteration algorithm is presented, which is based on a single sample
path, and eventually a special case in which parameters only
dominate the disturbance matrices will be analyzed, and a precise
comparison with be displayed between our algorithm with the old
ones which is aim to solve these problems in general Markov reward
processes. When applied in SPMRPs, our method will approach a fast
pace in these cases. Furthermore, to illustrate the practical value of
SPMRPs, a simple example in multiple programming in computer
systems will be listed and simulated. Corresponding to some practical
model, physical meanings of SPMRPs in networks of queues will be
clarified.