scholarly journals Research Design Of An Adaptive Controller Based On Desired Trajectory Compensation Of Neural Networks

2014 ◽  
Vol 14 (5) ◽  
pp. 5-16
Author(s):  
Liu Yu
Keyword(s):  
Neural Networks ◽  
Closed Loop ◽  
Variable Structure ◽  
Lyapunov Stability Theory ◽  
Adaptive Controller ◽  
Continuous Variable ◽  
Theoretic Analysis ◽  
Structure Control ◽  
The Neural Network ◽  
Neural Network Input

Abstract This paper has designed a variable structure controller based on the nominal compensation of neural networks. The neural network input is the desired trajectory, which eliminates the strict assumptions of the control inputs in conventional neural networks. It also ensures the asymptotic stability of the system closed-loop global exponentials to introduce model compensation and continuous variable structure control rate. By means of Lyapunov stability theory, it is analyzed and researched how to guarantee good transient performance of the control system comprehensively and thoroughly. The theoretic analysis and simulation results demonstrate the efficiency of the method proposed.

SYNCHRONIZATION CONTROL OF NEURAL NETWORKS SUBJECT TO TIME-VARYING DELAYS AND INPUT NONLINEARITY

2006 ◽  
Vol 16 (12) ◽  
pp. 3643-3654 ◽  
Author(s):  
JUN-JUH YAN ◽  
TEH-LU LIAO ◽  
JUI-SHENG LIN ◽  
CHAO-JUNG CHENG
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Variable Structure ◽  
Hopfield Neural Network ◽  
Cellular Neural Network ◽  
Control Technique ◽  
Time Varying ◽  
Input Nonlinearity ◽  
Structure Control ◽  
Synchronization Problem

This paper investigates the synchronization problem for a particular class of neural networks subject to time-varying delays and input nonlinearity. Using the variable structure control technique, a memoryless decentralized control law is established which guarantees exponential synchronization even when input nonlinearity is present. The proposed controller is suitable for application in delayed cellular neural networks and Hopfield neural networks with no restriction on the derivative of the time-varying delays. A two-dimensional cellular neural network and a four-dimensional Hopfield neural network, both with time-varying delays, are presented as illustrative examples to demonstrate the effectiveness of the proposed synchronization scheme.

scholarly journals Robust Controller Design for Modified Projective Synchronization of Chen-Lee Chaotic Systems with Nonlinear Inputs

2009 ◽  
Vol 2009 ◽  
pp. 1-10 ◽  
Author(s):  
Jui-sheng Lin ◽  
Neng-Sheng Pai ◽  
Her-Terng Yau
Keyword(s):  
Chaotic Systems ◽  
Controller Design ◽  
Sufficient Conditions ◽  
Variable Structure ◽  
Lyapunov Stability Theory ◽  
Projective Synchronization ◽  
Nonlinear Controller ◽  
Input Nonlinearity ◽  
Structure Control ◽  
Modified Projective Synchronization

This study demonstrates the modified projective synchronization in Chen-Lee chaotic system. The variable structure control technology is used to design the synchronization controller with input nonlinearity. Based on Lyapunov stability theory, a nonlinear controller and some generic sufficient conditions can be obtained to guarantee the modified projective synchronization, including synchronization, antisynchronization, and projective synchronization in spite of the input nonlinearity. The numerical simulation results show that the synchronization and antisynchronization can coexist in Chen-Lee chaotic systems. It demonstrates the validity and feasibility of the proposed controller.

Vehicle Traction Control: Variable-Structure Control Approach

1991 ◽  
Vol 113 (2) ◽  
pp. 223-230 ◽  
Author(s):  
Han-Shue Tan ◽  
Yuen-Kwok Chin
Keyword(s):  
Sliding Mode ◽  
Control Variable ◽  
Sufficient Conditions ◽  
Variable Structure ◽  
Lyapunov Stability Theory ◽  
Vehicle Model ◽  
Control Laws ◽  
Traction Control ◽  
Control Approach ◽  
Structure Control

A longitudinal one-wheel vehicle model is described for both anti-lock braking and anti-span acceleration. Based on this vehicle model, sufficient conditions for applying sliding-mode control to vehicle traction are derived via Lyapunov Stability Theory. With the understanding of these sufficient conditions, control laws are designed to control vehicle traction. Both the sufficient conditions and the control laws are verified using computer simulations.

A GPVSC Controller for Batch Dyeing Process Based on Integrated Model

2013 ◽  
Vol 433-435 ◽  
pp. 1065-1071
Author(s):  
Yong Xing Zhang ◽  
Jian Xin Zhang
Keyword(s):  
Control System ◽  
Uptake Rate ◽  
Closed Loop ◽  
Variable Structure ◽  
Closed Loop Control ◽  
Loop Control ◽  
Structure Control ◽  
Dyeing Process ◽  
Closed Loop Control System ◽  
Loop Control System

Traditional textile dyeing industry, which is always based on open-loop control strategy, has the problem of high energy consumption and serious pollution because it is difficult to deal with the direct control problem of the dyeing process. Based on the multi-variable dyeing uptake rate integration model, this paper proposed a closed loop control system using Generalized Prediction Variable Structure Control (GPVSC) algorithm. The integrated model is used as the soft measurement method of the whole closed loop control system, which can solve the problem that it is hard to measure dyeing uptake rate directly during the batch dyeing process. In the aspect of control algorithm, the Generalized Prediction Controller (GPC) was combined with Variable Structure Control (VSC), where the temperature was selected as the control variable, which achieved the control of the dyeing uptake rate during the batch dyeing process. Simulation results show that the algorithm could exactly track and control the dyeing uptake rate during the batch dyeing process.

scholarly journals Robust adaptive controller design for excavator arm

2019 ◽  
Vol 8 (4) ◽  
pp. 293
Author(s):  
Nga Thi-Thuy Vu
Keyword(s):  
Closed Loop ◽  
Controller Design ◽  
Lyapunov Stability Theory ◽  
Adaptive Controller ◽  
Closed Loop System ◽  
Model Free ◽  
Lagrange Form ◽  
Robust Adaptive ◽  
The Stability ◽  
Robust Adaptive Controller

This paper presents a robust adaptive controller that does not depend on the system parameters for an excavator arm. Firstly, the model of the excavator arm is demonstrated in the Euler-Lagrange form considering with overall excavator system. Next, a robust adaptive controller has been constructed from information of state error. In this paper, the stability of overall system is mathematically proven by using Lyapunov stability theory. Also, the proposed controller is model free then the closed loop system is not affected by disturbances and uncertainties. Finally, the simulation is executed in Matlab/Simulink for both presented scheme and the PD controller under some conditions to ensure that the proposed algorithm given the good performances for all cases.

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