We consider the problem of minimizing the worst asymptotic output variance of a control system if the disturbances are restricted to set-constraints on their covariance coefficients only. We reveal how one simple Lagrange duality argument allows the re-formulation as a parameterized positive real design problem. As the main contribution, we provide a direct solution of this parameterized positi...

Design of adaptive backstepping control for stabilization and synchronization a class uncertain fractional-order chaotic systems with uncertainties disturbances

an asymptotically stable direct adaptive fuzzy pi sliding modecontroller is proposed for a class of nonlinear uncertain systems. in contrast toother existing approaches of handling disturbances, the proposed approachdoes not require this bound to be known, only requiring that it exists.moreover, a pi control structure is used to attenuate chattering. the approachis applied to stabilize an open-...

This paper deals with leader-following and leaderless consensus problems of high-order multi-input/multi-output (MIMO) multi-agent systems with unknown nonlinear dynamics in the presence of uncertain external disturbances. The agents may have different dynamics and communicate together under a directed graph. A distributed adaptive method is designed for both cases. The structures of the contro...

This paper proposes an output-feedback sliding mode control design for a class of uncertain multivariable plants with nonlinear disturbances. The approach used here is based on the control parameterization employed in model-reference adaptive control. The disturbances are allowed to be unmatched and to depend not only on the plant output but also on its unmeasurable state. A less restrictive co...

Prediction-based Iterative Learning Control (PILC) is proposed in this paper for a class of time varying nonlinear uncertain systems. Convergence of PILC is analyzed and the uniform boundedness of tracking error is obtained in the presence of uncertainty and disturbances. It is shown that the learning algorithm not only guarantees the robustness, but also improves the learning rate despite the ...

In this paper the problem of practical stabilization for a significant class of MIMO uncertain pseudo-linear and pseudoquadratic systems, with additional bounded nonlinearities and/or bounded disturbances, is considered. By using the concept of majorant system, via Lyapunov approach, new fundamental theorems, from which derive explicit formulas to design state feedback control laws, with a poss...