91,288 research outputs found
Numerical solution of a fuzzy time-optimal control problem
In this paper, we consider a time-optimal control problem with uncertainties.
Dynamics of controlled object is expressed by crisp linear system of
differential equations with fuzzy initial and final states. We introduce a
notion of fuzzy optimal time and reduce its calculation to two crisp optimal
control problems. We examine the proposed approach on an example.Comment: 11 pages, 3 figure
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A note on the robust stability of uncertain stochastic fuzzy systems with time-delays
Copyright [2004] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.Takagi-Sugeno (T-S) fuzzy models are now often used to describe complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning applied to a set of linear submodels. In this note, the T-S fuzzy model approach is exploited to establish stability criteria for a class of nonlinear stochastic systems with time delay. Sufficient conditions are derived in the format of linear matrix inequalities (LMIs), such that for all admissible parameter uncertainties, the overall fuzzy system is stochastically exponentially stable in the mean square, independent of the time delay. Therefore, with the numerically attractive Matlab LMI toolbox, the robust stability of the uncertain stochastic fuzzy systems with time delays can be easily checked
A survey on fuzzy fractional differential and optimal control nonlocal evolution equations
We survey some representative results on fuzzy fractional differential
equations, controllability, approximate controllability, optimal control, and
optimal feedback control for several different kinds of fractional evolution
equations. Optimality and relaxation of multiple control problems, described by
nonlinear fractional differential equations with nonlocal control conditions in
Banach spaces, are considered.Comment: This is a preprint of a paper whose final and definite form is with
'Journal of Computational and Applied Mathematics', ISSN: 0377-0427.
Submitted 17-July-2017; Revised 18-Sept-2017; Accepted for publication
20-Sept-2017. arXiv admin note: text overlap with arXiv:1504.0515
Nonlinear and sampled data control with application to power systems
Sampled data systems have come into practical importance for a variety of reasons.
The earliest of these had primarily to do with economy of design. A more recent surge of interest
was due to increase utilization of digital computers as controllers in feedback systems. This thesis
contributes some control design for a class of nonlinear system exhibition linear output. The
solution of several nonlinear control problems required the cancellation of some intrinsic dynamics
(so-called zero dynamics) of the plant under feedback. It results that the so-dened control will
ensure stability in closed-loop if and only if the dynamics to cancel are stable. What if those
dynamics are unstable? Classical control strategies through inversion might solve the problem while
making the closed loop system unstable. This thesis aims to introduce a solution for such a problem.
The main idea behind our work is to stabilize the nonminimum phase system in continuous- time
and undersampling using zero dynamics concept. The overall work in this thesis is divided into
two parts. In Part I, we introduce a feedback control designs for the input-output stabilization
and the Disturbance Decoupling problems of Single Input Single Output nonlinear systems. A
case study is presented, to illustrate an engineering application of results. Part II illustrates the
results obtained based on the Articial Intelligent Systems in power system machines. We note
that even though the use of some of the AI techniques such as Fuzzy Logic and Neural Network
does not require the computation of the model of the application, but it will still suer from some
drawbacks especially regarding the implementation in practical applications. An alternative used
approach is to use control techniques such as PID in the approximated linear model. This design
is very well known to be used, but it does not take into account the non-linearity of the model. In
fact, it seems that control design that is based on nonlinear control provide better performances
Solving P - Norm Intuitionistic Fuzzy Programming Problem
In this paper, notion of p - norm generalized trapezoidal intuitionistic
fuzzy numbers is introduced. A new ranking method is introduced for p - norm
generalized trapezoidal intuitionistic fuzzy numbers. Also we consider linear
programming problem in intuitionistic fuzzy environment. In this problem, all
the coefficients and variables are represented by p - norm generalized
trapezoidal intuitionistic fuzzy numbers. To overcome the limitations of the
existing methods, a new method is proposed to compute the intuitionistic fuzzy
optimal solution for intuitionistic fuzzy linear programming problem. An
illustrative numerical example is solved to demonstrate the efficiency of the
proposed approach.Comment: some erro
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