Abstract: This paper examines the problem of designing robust H controllers for for HIV/AIDS infection system with dual drug dosages described by a Takagi-Sugeno (S) fuzzy model. Based on a linear matrix inequality (LMI) approach, we develop an H controller which guarantees the L2-gain of the mapping from the exogenous input noise to the regulated output to be less than some prescribed value for the system. A sufficient condition of the controller for this system is given in term of Linear Matrix Inequalities (LMIs). The effectiveness of the proposed controller design methodology is finally demonstrated through simulation results. It has been shown that the anti-HIV vaccines are critically important in reducing the infected cells.
Abstract: This paper deals with the synthesis of fuzzy controller
applied to a permanent magnet synchronous machine (PMSM) with a
guaranteed H∞ performance. To design this fuzzy controller,
nonlinear model of the PMSM is approximated by Takagi-Sugeno
fuzzy model (T-S fuzzy model), then the so-called parallel
distributed compensation (PDC) is employed. Next, we derive the
property of the H∞ norm. The latter is cast in terms of linear matrix
inequalities (LMI-s) while minimizing the H∞ norm of the transfer
function between the disturbance and the error ( ) ev T . The
experimental and simulations results were conducted on a permanent
magnet synchronous machine to illustrate the effects of the fuzzy
modelling and the controller design via the PDC.
Abstract: In this paper, the robust exponential stability problem of discrete-time uncertain stochastic neural networks with timevarying delays is investigated. By introducing a new augmented Lyapunov function, some delay-dependent stable results are obtained in terms of linear matrix inequality (LMI) technique. Compared with some existing results in the literature, the conservatism of the new criteria is reduced notably. Three numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed method.
Abstract: In this paper, based on linear matrix inequality (LMI), by using Lyapunov functional theory, the exponential stability criterion is obtained for a class of uncertain Takagi-Sugeno fuzzy Hopfield neural networks (TSFHNNs) with time delays. Here we choose a generalized Lyapunov functional and introduce a parameterized model transformation with free weighting matrices to it, these techniques lead to generalized and less conservative stability condition that guarantee the wide stability region. Finally, an example is given to illustrate our results by using MATLAB LMI toolbox.
Abstract: In this paper we propose a new criterion for solving
the problem of channel shortening in multi-carrier systems. In a
discrete multitone receiver, a time-domain equalizer (TEQ) reduces
intersymbol interference (ISI) by shortening the effective duration of
the channel impulse response. Minimum mean square error (MMSE)
method for TEQ does not give satisfactory results. In [1] a new
criterion for partially equalizing severe ISI channels to reduce the
cyclic prefix overhead of the discrete multitone transceiver (DMT),
assuming a fixed transmission bandwidth, is introduced. Due to
specific constrained (unit morm constraint on the target impulse
response (TIR)) in their method, the freedom to choose optimum
vector (TIR) is reduced. Better results can be obtained by avoiding
the unit norm constraint on the target impulse response (TIR). In
this paper we change the cost function proposed in [1] to the cost
function of determining the maximum of a determinant subject to
linear matrix inequality (LMI) and quadratic constraint and solve the
resulting optimization problem. Usefulness of the proposed method
is shown with the help of simulations.
Abstract: In this paper, some brief sufficient conditions for the stability of FO-LTI systems dαx(t) dtα = Ax(t) with the fractional order are investigated when the matrix A and the fractional order α are uncertain or both α and A are uncertain, respectively. In addition, we also relate the stability of a fractional-order system with order 0 < α ≤ 1 to the stability of its equivalent fractional-order system with order 1 ≤ β < 2, the relationship between α and β is presented. Finally, a numeric experiment is given to demonstrate the effectiveness of our results.
Abstract: Repetitive systems stand for a kind of systems that
perform a simple task on a fixed pattern repetitively, which are
widely spread in industrial fields. Hence, many researchers have been
interested in those systems, especially in the field of iterative learning
control (ILC). In this paper, we propose a finite-horizon tracking
control scheme for linear time-varying repetitive systems with uncertain
initial conditions. The scheme is derived both analytically
and numerically for state-feedback systems and only numerically for
output-feedback systems. Then, it is extended to stable systems with
input constraints. All numerical schemes are developed in the forms
of linear matrix inequalities (LMIs). A distinguished feature of the
proposed scheme from the existing iterative learning control is that
the scheme guarantees the tracking performance exactly even under
uncertain initial conditions. The simulation results demonstrate the
good performance of the proposed scheme.