The LQG Control Algorithms for Nonlinear Dynamic Systems

Adaptive Fuzzy Dynamic Sliding Mode Control of Nonlinear Systems

Two phenomena can produce chattering: switching of input control signal and the large amplitude of this switching (switching gain). To remove the switching of input control signal, dynamic sliding mode control (DSMC) is used. In DSMC switching is removed due to the integrator which is placed before the plant. However, in DSMC the augmented system (system plus the integrator) is one dimension bi...

Dynamic Sliding Mode Control of Nonlinear Systems Using Neural Networks

Dynamic sliding mode control (DSMC) of nonlinear systems using neural networks is proposed. In DSMC the chattering is removed due to the integrator which is placed before the input control signal of the plant. However, in DSMC the augmented system is one dimension bigger than the actual system i.e. the states number of augmented system is more than the actual system and then to control of such ...

Neural Control for Nonlinear Dynamic Systems

A neural network based approach is presented for controlling two distinct types of nonlinear systems. The first corresponds to nonlinear systems with parametric uncertainties where the parameters occur nonlinearly. The second corresponds to systems for which stabilizing control structures cannot be determined. The proposed neural controllers are shown to result in closed-loop system stability u...

Comments on "Parallel Processing Algorithms for the Optimal Control of Nonlinear Dynamic Systems"

A Survey of Concurrency Control Algorithms in the Operating Systems

Concurrency control is one of the important problems in operation systems. Various studies have been reported to present different algorithms to address this problem, although a few attempts have been made to represent an overall view of the characteristics of these algorithms and comparison of their capabilities to each other. This paper presents a survey of the current methods for controlling...