COMPARISON OF AN X4-AUV PERFORMANCE USING A BACKSTEPPING AND INTEGRAL BACKSTEPPING APPROACH

2016 ◽  
Vol 78 (6-11) ◽  
Author(s):  
Nur Fadzillah Harun ◽  
Zainah Md. Zain
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Control Method ◽  
Underwater Vehicle ◽  
Control Technique ◽  
Underactuated System ◽  
Control Law ◽  
Backstepping Approach ◽  
Highly Nonlinear ◽  
Backstepping Controller ◽  
Propose Control System

X4-AUV is a type of an autonomous underwater vehicle (AUV) which has 4 inputs with six degrees of freedoms (6-DOFs) in motion and is classified under an underactuated system. Controlling an underactuated system is difficult tasks because of the highly nonlinear dynamic, uncertainties in hydrodynamics behaviour and mostly those systems fails to satisfy Brockett’s Theorem. It usually required nonlinear control technique and this paper proposed an integral backstepping controller for stabilizing an underactuated X4-AUV. A control law is designed for the system in new state space using integral backstepping. The performance of the proposed control method is examined through simulation and results demonstrate all motion is stabilized and convergence into desired point. We also compared the results with backstepping approach to see the effectiveness of the propose control system.

BACKSTEPPING CONTROLLER WITH PSO FOR AN UNDERACTUATED X4-AUV

2016 ◽  
Vol 78 (6-13) ◽  
Author(s):  
Nur Fadzillah Harun ◽  
Zainah Md. Zain
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Control Method ◽  
Fitness Function ◽  
Control Technique ◽  
Underactuated System ◽  
Effective Response ◽  
Control Approach ◽  
Comparison Results ◽  
Highly Nonlinear ◽  
Backstepping Controller

X4-AUV is a type of an autonomous underwater vehicle (AUV) which has 4 inputs with six degrees of freedoms (6-DOFs) in motion and is classified under an underactuated system. Controlling an underactuated AUV is difficult tasks because of the highly nonlinear dynamic, uncertainties in hydrodynamics behaviour and mostly those systems fails to satisfy Brockett’s Theorem. It usually required a nonlinear control approach and this paper proposed a backstepping control method with Particle Swarm Optimization (PSO) to stabilize an underactuated X4-AUV system. In backstepping controller design, accurate parameters are important in order to obtain the maximal and effective response. Hence, PSO is implemented to obtain optimal parameters for backstepping controller and its carry out by minimizing the fitness function. Comparison results illustrated the controller with PSO has a smooth and fast transient response into the desired point compared than manually tune controller parameters and also improve the system performances. The validity of the proposed control technique for an underactuated X4-AUV demonstrates through simulation.

scholarly journals NonlinearH∞Optimal Control Scheme for an Underwater Vehicle with Regional Function Formulation

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Zool H. Ismail ◽  
Matthew W. Dunnigan
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Tracking Error ◽  
Underwater Vehicle ◽  
Control Technique ◽  
Control Law ◽  
Parameter Uncertainties ◽  
External Disturbances ◽  
Control Scheme ◽  
Highly Nonlinear ◽  
Region Tracking

A conventional region control technique cannot meet the demands for an accurate tracking performance in view of its inability to accommodate highly nonlinear system dynamics, imprecise hydrodynamic coefficients, and external disturbances. In this paper, a robust technique is presented for an Autonomous Underwater Vehicle (AUV) with region tracking function. Within this control scheme, nonlinearH∞and region based control schemes are used. A Lyapunov-like function is presented for stability analysis of the proposed control law. Numerical simulations are presented to demonstrate the performance of the proposed tracking control of the AUV. It is shown that the proposed control law is robust against parameter uncertainties, external disturbances, and nonlinearities and it leads to uniform ultimate boundedness of the region tracking error.

Design and development of a backstepping controller autopilot for fixed-wing UAVs

2021 ◽  
pp. 1-27
Author(s):  
D. Sartori ◽  
F. Quagliotti ◽  
M.J. Rutherford ◽  
K.P. Valavanis
Keyword(s):  
Real Time ◽  
Control Law ◽  
Parametric Uncertainties ◽  
Hardware In The Loop ◽  
Aircraft Control ◽  
Backstepping Approach ◽  
Small Uav ◽  
Backstepping Controller ◽  
Definition Of ◽  
Performance Results

Abstract Backstepping represents a promising control law for fixed-wing Unmanned Aerial Vehicles (UAVs). Its non-linearity and its adaptation capabilities guarantee adequate control performance over the whole flight envelope, even when the aircraft model is affected by parametric uncertainties. In the literature, several works apply backstepping controllers to various aspects of fixed-wing UAV flight. Unfortunately, many of them have not been implemented in a real-time controller, and only few attempt simultaneous longitudinal and lateral–directional aircraft control. In this paper, an existing backstepping approach able to control longitudinal and lateral–directional motions is adapted for the definition of a control strategy suitable for small UAV autopilots. Rapidly changing inner-loop variables are controlled with non-adaptive backstepping, while slower outer loop navigation variables are Proportional–Integral–Derivative (PID) controlled. The controller is evaluated through numerical simulations for two very diverse fixed-wing aircraft performing complex manoeuvres. The controller behaviour with model parametric uncertainties or in presence of noise is also tested. The performance results of a real-time implementation on a microcontroller are evaluated through hardware-in-the-loop simulation.

H ∞ Based Adaptive Fuzzy Control of a Tower Crane System

2012 ◽  
Author(s):  
Mansour Karkoub ◽  
Tzu Sung Wu ◽  
Chien Ting Chen
Keyword(s):  
Fuzzy Control ◽  
Time Delays ◽  
Adaptive Fuzzy Control ◽  
Tracking Performance ◽  
Control Technique ◽  
Control Law ◽  
External Disturbances ◽  
Adaptive Fuzzy ◽  
Tower Crane ◽  
Highly Nonlinear

Tower cranes are very complex mechanical systems and have been the subject of research investigations for several decades. Research on tower cranes has focused on the development of dynamical models (linear and nonlinear) as well as control techniques to reduce the swaying of the payload. Inherently, the dynamical model of the tower crane is highly nonlinear and classified as under-actuated. The crane system has potentially six degrees of freedom but only three actuators. Also, the actuators are far from the payload which makes the system non-colocated. The dynamic model describing the motion of the payload from point to point is affected by uncertainties, time delays and external disturbances which may lead to inaccurate positioning, reduce safety and efficacy of the overall system. It is proposed here to use an H∞ based adaptive fuzzy control technique to control the swaying motion of a tower crane. This technique will overcome modeling inaccuracies, such as drag and friction losses, effect of time delayed disturbances, as well as parameter uncertainties. The proposed control law for payload positioning is based on indirect adaptive fuzzy control. A fuzzy model is used to approximate the dynamics of the tower crane; then, an indirect adaptive fuzzy scheme is developed for overriding the nonlinearities and time delays. The advantage of employing an adaptive fuzzy system is the use of linear analytical results instead of estimating nonlinear system functions with an online update law. The adaptive fuzzy scheme fuses a Variable Structure (VS) scheme to resolve the system uncertainties, and the external disturbances such that H∞ tracking performance is achieved. A control law is derived based on a Lyapunov criterion and the Riccati-inequality to compensate for the effect of the external disturbances on tracking error so that all states of the system are uniformly ultimately bounded (UUB). Therefore, the effect can be reduced to any prescribed level to achieve H∞ tracking performance. Simulations are presented here to illustrate the performance of the proposed control design.

Implementation of Intelligent Control System for Autonomous Underwater Vehicle

2014 ◽  
Vol 701-702 ◽  
pp. 704-710 ◽  
Author(s):  
Viacheslav Pshikhopov ◽  
Yuriy Chernukhin ◽  
Viktor Guzik ◽  
Mikhail Medvedev ◽  
Boris Gurenko ◽  
...  
Keyword(s):  
Control System ◽  
Motion Control ◽  
Intelligent Control ◽  
Autonomous Underwater Vehicle ◽  
Control Method ◽  
Underwater Vehicle ◽  
Intelligent Control System ◽  
Azov Sea ◽  
Complex Simulation ◽  
Point To Point

This paper introduces the implementation of intelligent motion control and planning for autonomous underwater vehicle (AUV). Previously developed control system features intelligent motion control and planning subsystem, based on artificial neural networks. It allows detecting and avoiding moving obstacles in front of the AUV. The motion control subsystem uses position-trajectory control method to position AUV, move from point to point and along given path with given speed. Control system was tested in the multi-module simulation complex. Simulation showed good results – AUV successfully achieved given goals avoiding collisions not only with static obstacles, but also with mobile ones. That allows using the proposed control system for the groups of vehicles. Besides simulation, control system was implemented in hardware. AUV prototype passed tests in Azov Sea and proved its efficiency.

scholarly journals Control of Chaos in Rate-Dependent Friction-Induced Vibration Using Adaptive Sliding Mode Control and Impulse Damper

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Ehsan Maani Miandoab ◽  
Aghil Yousefi-Koma ◽  
Saeed Hashemnia
Keyword(s):  
Sliding Mode Control ◽  
Control Method ◽  
Sliding Mode ◽  
Control Technique ◽  
Adaptive Sliding Mode Control ◽  
Control Law ◽  
Adaptive Sliding Mode ◽  
Chaotic Vibration ◽  
Mode Control ◽  
Rate Dependent

Two different control methods, namely, adaptive sliding mode control and impulse damper, are used to control the chaotic vibration of a block on a belt system due to the rate-dependent friction. In the first method, using the sliding mode control technique and based on the Lyapunov stability theory, a sliding surface is determined, and an adaptive control law is established which stabilizes the chaotic response of the system. In the second control method, the vibration of this system is controlled by an impulse damper. In this method, an impulsive force is applied to the system by expanding and contracting the PZT stack according to efficient control law. Numerical simulations demonstrate the effectiveness of both methods in controlling the chaotic vibration of the system. It is shown that the settling time of the controlled system using impulse damper is less than that one controlled by adaptive sliding mode control; however, it needs more control effort.

scholarly journals Comparison of a Triple Inverted Pendulum Stabilization Using Optimal Control Technique

2020 ◽  
Author(s):  
Mustefa Jibril ◽  
Messay Tadese ◽  
Eliyas Alemayehu Tadese
Keyword(s):  
Optimal Control ◽  
Impulse Response ◽  
Inverted Pendulum ◽  
Control Method ◽  
Pole Placement ◽  
Control Technique ◽  
Comparison Results ◽  
Highly Nonlinear ◽  
Pole Placement Controller ◽  
Triple Inverted Pendulum

In this paper, modelling design and analysis of a triple inverted pendulum have been done using Matlab/Script toolbox. Since a triple inverted pendulum is highly nonlinear, strongly unstable without using feedback control system. In this paper an optimal control method means a linear quadratic regulator and pole placement controllers are used to stabilize the triple inverted pendulum upside. The impulse response simulation of the open loop system shows us that the pendulum is unstable. The comparison of the closed loop impulse response simulation of the pendulum with LQR and pole placement controllers results that both controllers have stabilized the system but the pendulum with LQR controllers have a high overshoot with long settling time than the pendulum with pole placement controller. Finally the comparison results prove that the pendulum with pole placement controller improve the stability of the system.

scholarly journals Iterative Self-Tuning Minimum Variance Control of a Nonlinear Autonomous Underwater Vehicle Maneuvering Model

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2686
Author(s):  
Maria Tomas-Rodríguez ◽  
Elías Revestido Herrero ◽  
Francisco J. Velasco
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Control Method ◽  
Linear Time ◽  
Control Design ◽  
Underwater Vehicle ◽  
Minimum Variance ◽  
Use Of Self ◽  
Self Tuning ◽  
Heading Angle ◽  
Iteration Technique

This paper addresses the problem of control design for a nonlinear maneuvering model of an autonomous underwater vehicle. The control algorithm is based on an iteration technique that approximates the original nonlinear model by a sequence of linear time-varying equations equivalent to the original nonlinear problem and a self-tuning control method so that the controller is designed at each time point on the interval for trajectory tracking and heading angle control. This work makes use of self-tuning minimum variance principles. The benefit of this approach is that the nonlinearities and couplings of the system are preserved, unlike in the cases of control design based on linearized systems, reducing in this manner the uncertainty in the model and increasing the robustness of the controller. The simulations here presented use a torpedo-shaped underwater vehicle model and show the good performance of the controller and accurate tracking for certain maneuvering cases.

scholarly journals Genetic Algorithm-Based Tuning of Backstepping Controller for a Quadrotor-Type Unmanned Aerial Vehicle

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1735
Author(s):  
Omar Rodríguez-Abreo ◽  
Juan Manuel Garcia-Guendulain ◽  
Rodrigo Hernández-Alvarado ◽  
Alejandro Flores Rangel ◽  
Carlos Fuentes-Silva
Keyword(s):  
Genetic Algorithms ◽  
Unmanned Aerial Vehicle ◽  
Control Technique ◽  
Design Parameters ◽  
System Response ◽  
Control Law ◽  
Self Tuning ◽  
Aerial Vehicle ◽  
Design Requirements ◽  
Backstepping Controller

Backstepping is a control technique based on Lyapunov’s theory that has been successfully implemented in the control of motors and robots by several nonlinear methods. However, there are no standardized methods for tuning control gains (unlike the PIDs). This paper shows the tuning gains of the backstepping controller, using Genetic Algorithms (GA), for an Unmanned Aerial Vehicle (UAV), quadrotor type, designed for autonomous trajectory tracking. First, a dynamic model of the vehicle is obtained through the Newton‒Euler methodology. Then, the control law is obtained, and self-tuning is performed, through which we can obtain suitable values of the gains in order to achieve the design requirements. In this work, the establishment time and maximum impulse are considered as such. The tuning and simulations of the system response were performed using the MATLAB-Simulink environment, obtaining as a result the compliance of the design parameters and the correct tracking of different trajectories. The results show that self-tuning by means of genetic algorithms satisfactorily adjusts for the gains of a backstepping controller applied to a quadrotor and allows for the implementation of a control system that responds appropriately to errors of different magnitude.

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