Dynamic Neural Networks for Model-Free Control and Identification

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 ...

Iterative learning identification and control for dynamic systems described by NARMAX model

A new iterative learning controller is proposed for a general unknown discrete time-varying nonlinear non-affine system represented by NARMAX (Nonlinear Autoregressive Moving Average with eXogenous inputs) model. The proposed controller is composed of an iterative learning neural identifier and an iterative learning controller. Iterative learning control and iterative learning identification ar...

Modeling and Control of Gas Turbine Combustor with Dynamic and Adaptive Neural Networks (TECHNICAL NOTE)

On Neural Networks in Identification and Control of Dynamic Systems

The paper presents a discussion on the applicability of neural networks in the identification a n d control of dynamic systems. Emphasis is placed on the understanding of how the neural networks handle linear systems a n d how the new approach is related to conventional system identification and control methods. Extensions of the approach to non-linear systems a r e then made. The paper explain...

Intelligent Control for Model-free Robot Joint with Dynamic Friction Using Wavelet Neural Networks

In this article, an intelligent compensation control algorithm for low-speed robot joint with dynamic friction was proposed based on self-recurrent wavelet neural networks (SRWNN). It is not necessary to predict the dynamic model parameters, and the high-precision compensation of nonlinear friction is realized by using few neurons and iterations through only position feedback. Lyapunov stabilit...