The paper deals with a class of semi-Markov control models with Borel state and control spaces, possibly unbounded costs, and unknown holding times distribution H. Assuming that H does not depend on state-action pairs, we combine suitable methods of statistical estimation of H with control...

This paper is concerned with decentralized tracking-type games for large population multi-agent systems with mean-field coupling. The individual dynamics are described by stochastic discrete-time auto-regressive models with exogenous inputs (ARX models), and coupled by terms of the unknown...

This paper presents an adaptive control scheme for a hyper-redundant robot articulated nimble adaptable trunk (ANAT) subject to spatial constraints. An optimization scheme is applied to avoid obstacles in 3D space present in the robot's trajectory by using redundancy, and to prevent the robot...

This paper presents an indirect adaptive control scheme for nominally stabilizable, non-necessarily inversely stable, first-order continuous-time systems with unmodeled dynamics. The control objective is the adaptive stabilization of the closed-loop system with a bounded tracking error between...

Cascade control configurations offer interesting possibilities to improve the control of processes. However, the tuning of cascade controllers can be quite complex, which hampers a wider spread of applications. Using an on-line pattern recognition approach and fuzzy inferencing it is possible to...

In this paper, we study perturbed Chua’s system. First, we study the stability of equilibrium points of perturbed Chua’s system. Then, we control the chaotic behavior of perturbed Chua’s system to its equilibrium points using linear feedback control and adaptive control methods. Finally,...

We address the problem of control and synchronization of a class of uncertain chaotic systems. Our approach follows techniques of sliding mode control and adaptive estimation law. The adaptive algorithm is constructed based on the sliding mode control to ensure perfect tracking and...

A neural network-based robust adaptive control design scheme is developed for a class of nonlinear systems represented by input–output models with an unknown nonlinear function and unmodeled dynamics. By on-line approximating the unknown nonlinear functions and unmodeled dynamics by radial...

Using the Lyapunov stability theory an adaptive control is proposed for chaos synchronization between two Chua systems which have stochastically time varying unknown coefficients. The stochastic variations of the coefficients around their unknown mean values are modeled through Gaussian white...

The objective of this paper is to present a survey on extremum seeking control methods and their applications to process and reaction systems. Two important classes of extremum seeking control approaches are considered: perturbation-based and model-based methods.