Search

In this paper, the l 2 − l ∞ state estimation problem of discrete-time nonlinear systems (DTNSs) with time-varying delay is studied. The main objective of this paper is to design a state estimator that guarantees not only the global h -stability of the error system in the absence of interference, but also that the output peak value of the error system remains within a certain range under the zero initial conditions. A direct analysis method based on the system solutions is presented, which gives a sufficient condition to decide whether the designed state estimator satisfies the expectation. The method does not follow the construct of any Lyapunov–Krasovskii functional (LKF), thus greatly reducing the workload and complexity of calculation. Finally, three simulation examples are presented to illustrate the applicability of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of H ∞ fuzzy filter design in finite frequency intervals for discrete-time nonlinear systems subject to time-varying delays. Fuzzy filters whose order is greater (non-minimal) than the order of the system are synthesized by transforming the original time-delayed system into an equivalent switched nonlinear system. The design conditions are given in terms of sufficient parameter-dependent linear matrix inequalities that can be solved through relaxations based on semi-definite programming. The advantages of the proposed approach are illustrated through numerical examples and comparisons with other available techniques. [ABSTRACT FROM AUTHOR]

This paper considers the problem of state bounding for homogeneous positive systems of degree one with time-varying delay and exogenous input. In both the continuous-time case and the discrete-time case, necessary and sufficient conditions are derived for the existence of a ball where all the solutions of the system converge exponentially within. Numerical examples are also given to illustrate the obtained results. [ABSTRACT FROM AUTHOR]

This paper presents a new data-driven adaptive ILC (DDAILC) for a class of nonlinear discrete-time systems by introducing a pointwise dynamical linearization approach in the iteration direction. For the nonlinear systems, which cannot be linearly parameterized, the proposed DDAILC is capable of achieving a perfect performance without requiring any identical conditions exposed both on the initial state and on the reference trajectory. It is a data-driven control approach since only the I/O data is required for the control system design and analysis. The parameter updating law is constructed to estimate the inverse values of the system׳s unknown partial derivatives of the nonlinear system with respect to the control inputs, which are utilized to compute the learning gain of control law further. The control input is updated by using both the information of reference trajectory of the current operation as a feedback term and the input signals in previous operations as a feedforward term. Extension results to MIMO nonlinear discrete-time systems are provided further. Both theoretical analysis and simulation results verify the effectiveness of the proposed data-driven AILC approach. [ABSTRACT FROM AUTHOR]