Sampled-data output-feedback H∞ control of linear systems is considered. The only restriction on the sampling and hold is that the distances between the sequel sampling times and holding times are not greater than given bounds.A new approach, which was recently introduced to sampled-data state-feedback stabilization, is developed to the H∞ control. The system is modelled as a continuous-time on...

This paper addresses the robust consensus control design for input-delayed multi-agent systems subject to parametric uncertainties. To deal with the input delay, the Artstein model reduction method is employed by a state transformation. The input-dependent integral term that remains in the transformed system, due to the model uncertainties, is judiciously analysed. By carefully exploring certai...

For neural networks with constant or time-varying delays, the problems of determining the exponential stability and estimating the exponential convergence rate are studied in this paper. An approach combining the Lyapunov-Krasovskii functionals with the linear matrix inequality is taken to investigate the problems, which provide bounds on the interconnection matrix and the activation functions,...

In this paper, adaptive neural control is proposed for a class of multi-input multi-output (MIMO) nonlinear unknown state time-varying delay systems in block-triangular control structure. Radial basis function (RBF) neural networks (NNs) are utilized to estimate the unknown continuous functions. The unknown time-varying delays are compensated for using integral-type Lyapunov-Krasovskii function...

Funding information PROMETEOII/2013/004; Conselleria d'Educació; Generalitat Valenciana, Grant/Award Number: TIN2014-56158-C4-4-P-AR; Ministerio de Economía y Competitividad, Grant/Award Number: FPI-UPV 2014; Universitat Politècnica de València Summary The problem of output stabilization and disturbance rejection for input-delayed systems is tackled in this work. First, a suitable transformatio...

Approximation-based control is presented for a class of multi-input multi-output (MIMO) nonlinear systems in block-triangular form with unknown state delays. Neural networks (NNs) are utilized to approximate and compensate for unknown functions in the system dynamics, including the unknown bounds of the functions of delayed states. The use of a separation technique removes the need for any assu...

We study a sampled-data implementation of linear controllers that depend on the output and its derivatives. First, we consider an LTI system of relative degree r ≥ 2 that can be stabilized using r − 1 output derivatives. Then, we consider PID control of a second order system. In both cases, the Euler approximation is used for the derivatives giving rise to a delayed sampled-data controller. Giv...

In this paper, the problem of neutral-type impulsive bidirectional associative memory neural networks (NIBAMNNs) with time delays are first established by a Takagi–Sugeno (T-S) fuzzy model in which the consequent parts are composed of a set of NIBAMNNs with interval delays and Markovian jumping parameters (MJPs). Sufficient conditions to check the robust exponential stability of the derived mod...

In this note, adaptive neural control is presented for a class of strict-feedback nonlinear systems with unknown time delays. Using appropriate Lyapunov–Krasovskii functionals, the uncertainties of unknown time delays are compensated for such that iterative backstepping design can be carried out. In addition, controller singularity problems are solved by using the integral Lyapunov function and...

This paper proposes a novel adaptive fuzzy decentralized output-feedback control approach for a class of uncertain nonlinear large-scale systems. The considered nonlinear systems possess the unknown nonlinear functions, unmeasured states and unknown time-varying delays. Fuzzy logic systems are employed to approximate the unknown nonlinear functions, and adaptive high-gain filters are presented ...