scholarly journals Relook at Aileron to Rudder Interconnect

2021 ◽  
Vol 71 (2) ◽  
pp. 153-161
Author(s):  
M. Jayalakshmi ◽  
Vijay V. Patel ◽  
Giresk K. Singh
Keyword(s):  
Transfer Function ◽  
Surface Damage ◽  
Significant Part ◽  
Control Law ◽  
Feed Forward ◽  
Roll Rate ◽  
Aircraft System ◽  
Dutch Roll ◽  
Forward Gain ◽  
Lateral Axis

The implementation of interconnect gain from aileron to rudder surface on the majority of the aircraftis to decrease sideslip which is generated because of adverse yaw with the movement of control stick in lateral axis and also enhances the turning rate performance.The Aileron to Rudder Interconnect (ARI)involves significant part to decouple the Dutch roll oscillations from roll rate response to aileron command. ARI is feed-forward gain whichis susceptible to aircraft system uncertainty. Incorrect ARI gain can lead to side slip buildup which can cause aircraft to depart in case of fault scenarios. Four systematic ARI design methods are proposed. One of the proposed methods which use the norm of ARI transfer function at roll damping frequency is suitable for online reconfiguration of control law. The reconfiguration of ARI gain is illustratedwith the simulation responses of fault scenario case of aileron surface damage.

scholarly journals Research of Conventional and Observer Based Controller for Three Tank Interacting System

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1527-1531
Keyword(s):  
Pid Controller ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Control Law ◽  
Feed Forward ◽  
Single Input Single Output ◽  
Single Output ◽  
Control Scheme ◽  
Single Input ◽  
Forward Gain

In many Industries, the fault tolerant control scheme have been accepted and used from many decades. In this paper, the observer and the observer based Controller is designed for the three tank interacting system. Initially in this work, the three tank interacting system with Single Input Single Output configuration is modeled and conventional PID controller has been implemented, finally the performances are analyzed. Then the observer is designed for the three tank interacting system. Inorder to design the observer based controller, the control law and the feed forward gain value is calculated and described by Chakrabarti A et al.[4]. Finally the observer based controller performances are also analyzed. In this work, the sensor is replaced by the state observer. The observer based controller provides better performance than the conventional PID controller. This work may lead to design fault tolerant control for three tank interacting system in future.

Stabilizing and Swinging-Up the Inverted Pendulum Using PI and PID Controllers Based on Reduced Linear Quadratic Regulator Tuned by PSO

2015 ◽  
Vol 4 (4) ◽  
pp. 52-69 ◽  
Author(s):  
M. E. Mousa ◽  
M. A. Ebrahim ◽  
M. A. Moustafa Hassan
Keyword(s):  
Pid Controller ◽  
Inverted Pendulum ◽  
Research Work ◽  
Linear Quadratic Regulator ◽  
Nonlinear Problems ◽  
Pid Controllers ◽  
Linear Quadratic ◽  
Swarm Optimization ◽  
Feed Forward ◽  
Forward Gain

The inherited instabilities in the Inverted Pendulum (IP) system make it one of the most difficult nonlinear problems in the control theory. In this research work, Proportional –Integral and Derivative (PID) Controller with a feed forward gain is used with Reduced Linear Quadratic Regulator (RLQR) for stabilizing the Cart Position and Swinging-up the Pendulum angle. Tuning the Controllers' gains is achieved by using Particle Swarm Optimization (PSO) Technique. Obtaining the combined PID controllers' gains with a feed forward gain and RLQR is a multi-dimensions control problem. The Proposed Controllers give minimum Settling Time, Rise Time, Undershoot and Over shoot for both the Cart Position and the Pendulum angle. A disturbance with different amplitudes is applied to the system, and the results showed the robustness of the systems based on the tuned controllers. The overall results are promising.

Design of an adaptive control law using trigonometric functions for robot manipulators

Robotica ◽  
2005 ◽  
Vol 23 (1) ◽  
pp. 93-99 ◽  
Author(s):  
Recep Burkan
Keyword(s):  
Adaptive Control ◽  
Robot Manipulators ◽  
Tracking Error ◽  
Uncertain System ◽  
Control Law ◽  
Trigonometric Functions ◽  
Feed Forward ◽  
Inertia Parameters ◽  
The Stability ◽  
Adaptive Control Law

In this study, a new approach of adaptive control law for controlling robot manipulators using the Lyapunov based theory is derived, thus the stability of an uncertain system is guaranteed. The control law includes a PD feed forward part and a full dynamics feed forward compensation part with the unknown manipulator and payload parameters. The novelty of the obtained result is that an adaptive control algorithm is developed using trigonometric functions depending on manipulator kinematics, inertia parameters and tracking error, and both system parameters and adaptation gain matrix are updated in time.

Research on Accessibility of Integral Sliding Mode Contorl of Missile System

2011 ◽  
Vol 66-68 ◽  
pp. 212-216
Author(s):  
Wen Guang Zhang ◽  
Jun Wei Lei ◽  
Ling Ling Wang
Keyword(s):  
Control System ◽  
Transfer Function ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Control Law ◽  
Overload Control ◽  
Function Type ◽  
Dynamic Coefficients ◽  
Missile System ◽  
Backstepping Algorithm

Considering the no uncertain air-dynamic coefficients situation, a kind of sliding mode control law, which was composed of the angle velocity and overload error, was designed for the overload control system of missile. And the accessibility of sliding mode was analyzed. What worthy pointing out is that a transfer- function-type backstepping algorithm was adopted to solve the derivative item of actuator and a novel type of control was proposed.

scholarly journals APPLICATION OF LEARNING FEED-FORWARD CONTROLLER BASED ON MODEL REFERENCE ADAPTIVE SYSTEM FOR MISSILE STABILIZATION

2021 ◽  
Vol 1 (4(68)) ◽  
pp. 34-39
Author(s):  
V. Nguyen ◽  
C. Dang ◽  
V. Luong
Keyword(s):  
Adaptive System ◽  
Lyapunov Stability Theory ◽  
Control Law ◽  
Model Reference ◽  
Feed Forward ◽  
Model Reference Adaptive System ◽  
Feed Forward Controller ◽  
Model Reference Adaptive ◽  
Adaptive Control Law ◽  
Research Analysis

The article presents the results of research, analysis and how to build learning feed-forward controller based on model reference adaptive system in the remote control loop for missile stabilization. The controller structure is simple, adaptive control law applying Lyapunov stability theory fast convergence and sustainable. The simulation results have shown the advantages of using algorithm, the missile is always stable when there is a parameter change due to the effects of flight conditions.

scholarly journals The effects of multiple layers feed-forward neural network transfer function in digital based Ethiopian soil classification and moisture prediction

2020 ◽  
Vol 10 (4) ◽  
pp. 4073
Author(s):  
Belete Biazen Bezabeh ◽  
Abrham Debasu Mengistu
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Performance Analysis ◽  
Transfer Function ◽  
Soil Classification ◽  
Learning Performance ◽  
Machine Learning Techniques ◽  
Feature Descriptor ◽  
Feed Forward Neural Network ◽  
Feed Forward

In the area of machine learning performance analysis is the major task in order to get a better performance both in training and testing model. In addition, performance analysis of machine learning techniques helps to identify how the machine is performing on the given input and also to find any improvements needed to make on the learning model. Feed-forward neural network (FFNN) has different area of applications, but the epoch convergences of the network differs from the usage of transfer function. In this study, to build the model for classification and moisture prediction of soil, rectified linear units (ReLU), Sigmoid, hyperbolic tangent (Tanh) and Gaussian transfer function of feed-forward neural network had been analyzed to identify an appropriate transfer function. Color, texture, shape and brisk local feature descriptor are used as a feature vector of FFNN in the input layer and 4 hidden layers were considered in this study. In each hidden layer 26 neurons are used. From the experiment, Gaussian transfer function outperforms than ReLU, sigmoid and tanh transfer function. But the convergence rate of Gaussian transfer function took more epoch than ReLU, Sigmoid and tanh.

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