In this paper, a novel control method by using parallel online mixing and supplying technology for glue system with multi-input, strong coupling and nonlinear was provided. The neural network controller design method is adopted to design the intelligent controller, in which one as the main controller and the other one as the identifier to revise main controller. Both advantages and disadvantage...

this paper presents a new observer-based control scheme for a class of nonlinear systems. in the proposed method, nonlinear observer and twisting algorithm controller are employed to realize a sensor-less control strategy for complex systems which makes use of non measurable process information instead of installing as many sensors as possible. due to lack of availability of the complex system ...

The ever-growing use of various vehicles for transportation, on the one hand, and the statistics ofsoaring road accidents resulting from human error, on the other hand, reminds us of the necessity toconduct more extensive research on the design, manufacturing and control of driver-less intelligentvehicles. For the automatic control of an autonomous vehicle, we need its dynamic...

In this paper, a neural network based predictive controller is designed to govern the dynamics of a heat exchanger pilot plant. Heat exchanger is a highly nonlinear process; therefore, a nonlinear prediction method can be a better match in a predictive control strategy. Advantages of neural networks for the process modeling are studied and a neural network based predictor is designed, trained a...

Pneumatic actuation systems are widely used in industrial automation, such as drilling, sawing, squeezing, gripping, and spraying. Also, they are used in motion control of materials and parts handling, packing machines, machine tools, food processing industry and in robotics; e.g. two-legged robot. In this paper, a Neural Network based intelligent PI controller is designed and simulated to incr...

This paper presents an off-line (finite time interval) and on-line learning direct adaptive neural controller for an unstable helicopter. The neural controller is designed to track pitch rate command signal generated using the reference model. A helicopter having a soft inplane four-bladed hingeless main rotor and a four-bladed tail rotor with conventional mechanical controls is used for the si...

By using differential neural networks, we present a novel robust adaptive controller for a class of unknown nonlinear systems. First, dead-zone and projection techniques are applied to neural model, such that the identification error is bounded and the weights are different from zero. Then, a linearization controller is designed based on the neuro identifier. Since the approximation capability ...

Abstract: This paper investigates a novel recurrent neural network (NN)-based vector control approach for single-phase grid-connected converters (GCCs) with L (inductor), LC (inductor-capacitor) and LCL (inductor-capacitor-inductor) filters and provides their comparison study with the conventional standard vector control method. A single neural network controller replaces two current-loop PI co...

In this paper a new approach to a neural network-based model reference adaptive intelligent controller is proposed. In this scheme, the intelligent supervisory loop is incorporated into the conventional model reference adaptive controller framework by utilizing an online growing multilayer back propagation neural network structure in parallel with it. The idea is to control the plant by convent...

The use of a proposed recurrent neural network control system to control a four-legged walking robot is presented in this paper. The control system consists of a neural controller, a standard PD controller, and the walking robot. The robot is a planar four-legged walking robot. The proposed Neural Network (NN) is employed as an inverse controller of the robot. The NN has three layers, which are...