Backstepping Approach for Autonomous Mobile Robot Trajectory Tracking

Ibari, Benaoumeur; Benchikh, Laredj; Reda, Hanifi Elhachimi Amar; Ahmed‐Foitih, Zoubir

doi:10.11591/ijeecs.v2.i3.pp478-485

Cited by 15 publications

(10 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We will introduce a positive-definite function V k (t) = 1 2 ω(t) 2 + 1 2 z e (t) T z e (t) to analyze the stability of the kinematic controller. By substituting Equation 11 and using the relation J T = −J, we can obtain the time derivative of V k (t) as follows:V…”

Section: Kinematic Controllermentioning

confidence: 99%

See 1 more Smart Citation

A new adaptive tracking control scheme of wheeled mobile robot without longitudinal velocity measurement

Shu

Oya

Zhao

2017

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

This paper proposes a new adaptive trajectory tracking control scheme of the wheeled mobile robot without longitudinal velocity measurement. First, based on a kinematic controller, we obtain a new tracking error equation, which is suitable to develop an adaptive controller. Then, we develop a new adaptive trajectory tracking controller, which does not need any accurate values of the wheeled mobile robot parameters, including the driving motor parameters.Moreover, as the longitudinal velocity measurement is still difficult, this controller is developed without longitudinal velocity measurement. In addition, this new adaptive controller introduces a method to improve the control performance. The stability of the closed-loop system is presented using the direct Lyapunov method. Finally, numerous simulations verify the effectiveness of the new controller. KEYWORDSadaptive control, motor characteristics, trajectory tracking control, wheeled mobile robot INTRODUCTIONA wheeled mobile robot (WMR) is a typical kind of nonholonomic system. Research on trajectory tracking of the WMR has been attracting great attention. Because of the nonholonomic property of the WMR, the normal state feedback controller cannot be utilized to realize trajectory tracking for the WMR. 1 Therefore, in early works, trajectory tracking controllers were developed based on a kinematic model. [2][3][4][5][6][7][8]28 However, if there is no consideration of the dynamics of the WMR, it will be obvious that the control performances will be affected, especially when the WMR moves with a high velocity. Therefore, it is necessary to consider the dynamics of WMR to realize good trajectory tracking performance. To deal with this problem, trajectory tracking controllers, which consider the dynamics of WMR, have been proposed. 9-12 However, in previous works, [9][10][11][12] accurate knowledge of the WMR parameters is required. When there exist large unknown variations of the WMR parameter values, it will be difficult to realize the desired control performance. To solve this problem, controllers that have robustness against unknown variations of the WMR parameter values are proposed. [13][14][15][16][17] As an effective method to increase robustness, adaptive estimation is usually used, and it is also utilized in the works of Dixon et al 13 and Huang et al, 15 Yoo, 16 and Peng et al. 17 However, in these proposed controllers, the wheel torques are utilized as the control inputs. In practical applications, it is necessary to consider the characteristics of the driving motors, which generate the wheel torques. Based on this consideration, controllers that take into account the motor characteristics are proposed. [18][19][20][21] In these controllers, the measurements of position, yaw rate, and longitudinal velocity of the WMR are usually utilized. The position measurement can be realized by using high-accurate GPS or image processing technology. The yaw rate can be measured with a low-cost sensor, and the yaw rate measurements are widely used. The longitudina...

show abstract

Section: Kinematic Controllermentioning

confidence: 99%

“…To deal with this problem, trajectory tracking controllers, which consider the dynamics of WMR, have been proposed. 9-12 However, in previous works, [9][10][11][12] accurate knowledge of the WMR parameters is required. When there exist large unknown variations of the WMR parameter values, it will be difficult to realize the desired control performance.…”

mentioning

confidence: 99%

A new adaptive tracking control scheme of wheeled mobile robot without longitudinal velocity measurement

Shu

Oya

Zhao

2017

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…In the last decade, many researchers propose trajectory-tracking control for a mobile robot. Authors in [1][2][3] propose a backstepping controller design for trajectory tracking of unicycle-type mobile based on the Lyapunov theorem. In [4] a Linear Quadratic Controller (LQR) type based on the linearized model of the robot is proposed and simulation studies were conducted to determine its performance.…”

Section: Introductionmentioning

confidence: 99%

Control of mobile robot using fractional order PI<sup>λ</sup>D<sup>μ</sup> controller

2019

View full text Add to dashboard Cite

The ideal example for studying complex systems with non-holonomic constraints is mobile-wheeled robots. In this article, we study the problem of trajectory tracking of mobile robot unicycle type. To resolve this type of problem a fractional-order control technique is proposed. The main objective of this control method is to design a robust tracking controller to eliminate disturbances. The mathematical model of the mobile robot taken explicitly into account their dynamics is used to calculate the desired linear and angular velocities. To adjust the controller optimal parameters the particle swarm optimization (PSO) algorithm is utilized. The simulation results allowed us to demonstrate the efficiency and robustness of this technique on non-holonomic systems in the form of chained chains.

show abstract

“…Mainly the trajectory tracking control algorithms can be classified into on of six categories [1]: (1) backstepping [2], [3]; (2) linearization [4]; (3) sliding mode [5]; (4) fuzzy systems [6], [7]; (5) neural networks [8]; and (6) neurofuzzy systems [9].…”

Section: Introductionmentioning

confidence: 99%

Real Time Trajectory Tracking Controller based on Lyapunov Function for Mobile Robot

Elsayed¹,

Hammad²,

Hafez³

et al. 2017

IJCA

View full text Add to dashboard Cite

An important issue in robotics research is path tracking control where the robot is required to follow a certain path. The error between the desired path and the actual path is to converge to zero. This problem is more complicated when the robot dynamics is considered. This paper proposes a real time trajectory tracking control for a differential drive wheeled mobile robot (DDWMR) in obstacle-free environment. The robot is guided to follow certain reference path with a pre-calculated velocity profile. The controller design and analysis of the system stability are guaranteed using Lyapunov stability theory. The dynamic model of real DDWMR is derived and used in the LabVIEW simulation environment for testing the validity of designed controller. The obtained simulation results illustrate the success of the proposed controller. Also to Test the effectiveness of proposed controller, a comparison study with a widely used backstepping based controller is performed.

show abstract

Backstepping Approach for Autonomous Mobile Robot Trajectory Tracking

Cited by 15 publications

References 24 publications

A new adaptive tracking control scheme of wheeled mobile robot without longitudinal velocity measurement

A new adaptive tracking control scheme of wheeled mobile robot without longitudinal velocity measurement

Control of mobile robot using fractional order PI<sup>λ</sup>D<sup>μ</sup> controller

Real Time Trajectory Tracking Controller based on Lyapunov Function for Mobile Robot

Contact Info

Product

Resources

About