A Simple Adaptive Control Approach for Trajectory Tracking of Electrically Driven Nonholonomic Mobile Robots

Park, Bong Seok; Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho

doi:10.1109/tcst.2009.2034639

Cited by 221 publications

(114 citation statements)

References 26 publications

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“…(1) and (2) are no longer true. Now let γ R and γ L denote the coordinates of the longitudinal slip of the right and left wheels, respectively, and η denote the coordinate of the lateral slip along the wheel shaft (see Figure 1a).…”

Section: The Kinematics Of a Nonholonomic Wmr In The Presence Of Wheementioning

confidence: 99%

“…In recent years, due to the fact that wheeled mobile robots (WMRs) are widely applied and increasingly popular, a lot of the effort of researchers in the world has been spent to solve the tracking control problems of WMRs by using various control techniques such as sliding mode control [1], adaptive control [2], and backstepping control [3,4]. All these works have been performed with an assumption that WMRs move on the floor without wheel slips.…”

Section: Introductionmentioning

confidence: 99%

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Neural network-based adaptive tracking control for a nonholonomic wheeled mobile robot with unknown wheel slips, model uncertainties, and unknown bounded disturbances

Nguyen¹,

Liu²

2018

Turk J Elec Eng & Comp Sci

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Abstract:In this paper, an adaptive tracking controller based on a three-layer neural network (NN) with an online weight tuning algorithm is proposed for a nonholonomic wheeled mobile robot in the presence of unknown wheel slips, model uncertainties, and unknown bounded disturbances. The online weight tuning algorithm is modified from the backpropagation with an e -modification term required to assure that the NN weights are bounded. Preliminary neural network offline training is not essential for the weights. Thanks to this proposed controller, the desired tracking performance is achieved where position tracking errors converge to an arbitrarily small neighborhood of the origin regardless of their initial values. According to Lyapunov theory and LaSalle extension, the stability of the whole closedloop system is ensured to obtain the desired tracking performance. Computer simulations are implemented to certify the validity of the proposed controller.

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Section: The Kinematics Of a Nonholonomic Wmr In The Presence Of Wheementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Neural network-based adaptive tracking control for a nonholonomic wheeled mobile robot with unknown wheel slips, model uncertainties, and unknown bounded disturbances

Nguyen¹,

Liu²

2018

Turk J Elec Eng & Comp Sci

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“…Some researchers tackled tracking and stabilization problems separately. See [28,29,30,31], for tracking problems, and [32,33,34] for stabilization problems. The trajectory tracking problem for nonholonomic vehicles has been tackled by transverse function approach [35].…”

Section: Introductionmentioning

confidence: 99%

Linear Time-Varying Feedback Law for Vehicles With Ackermann Steering

Miah¹,

Farkas²,

Gueaieb³

et al. 2017

International Journal of Robotics and Automation

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In this paper, we propose an optimal state feedback control law for addressing point stabilization and tracking problems of nonholonomic vehicles with Ackermann steering in a unified manner. Unlike other feedback controllers that perform dynamic linearization of vehicle models, the proposed optimal feedback controller provides the state feedback control to the original nonlinear vehicle model for achieving excellent state-tracking performance.In addition, nonlinear control techniques suggested in the literature to date require that the desired trajectory of the robot is generated using persistently excited inputs. This may be too restrictive and non-realistic hypothesis to mimic a real scenario. Here, we address this issue by developing a smooth state-feedback control law that is formulated by modifying the classical Pontryagin's minimum principle. The proposed control law can be applied for solving control problems of a general class of nonlinear affine systems. The proposed control scheme offers a modular solution to other control techniques for a large number of mobile robot applications. The theoretical results are validated through computer simulations.

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“…For wheeled mobile robots, conventional control laws have been applied for solving tracking problems [58,30,32,43,1,23,49] and stabilization problems [3,17,51,54,8]. For example, see [29,28,39,48,12,14] for backstepping methods [11,24,53] for sliding mode control, [9,34,18] for moving horizon H ∞ tracking control coupled with disturbance effect, and [47] for transverse function approach.…”

Section: Introductionmentioning

confidence: 99%

RFID-Based Mobile Robot Trajectory Tracking and Point Stabilization Through On-line Neighboring Optimal Control

Miah

Gueaieb

2014

J Intell Robot Syst

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In this manuscript, we propose an on-line trajectorytracking algorithm for nonholonomic Differential-Drive Mobile Robots (DDMRs) in the presence of possibly large parametric and measurement uncertainties. Most mobile robot tracking techniques that depend on reference RF beacons rely on approximating line-of-sight (LOS) distances between these beacons and the robot. The approximation of LOS is mostly performed using Received Signal Strength (RSS) measurements of signals propagating between the robot and RF beacons. However, accurate mapping between RSS measurements and LOS distance remains a significant challenge and is almost impossible to achieve in an indoor reverberant environment. This paper contributes to the development of a neighboring optimal control strategy where the two major control tasks, trajectory tracking and point stabilization, are solved and treated as a unified manner using RSS measurements emitted from Radio Frequency IDentification (RFID) tags. The proposed control scheme is divided into two cascaded phases. The first phase provides the robot's nominal control inputs (speeds) and its trajectory using full-state feedback. In the second phase, we design the neighboring optimal controller, where RSS measurements are used to better estimate the robot's pose by employing an optimal filter. Simulation and experimental results are presented to demonstrate the performance of the proposed optimal feedback controller for solving the stabilization and trajectory tracking problems using a DDMR. Keywords Mobile robot navigation · RFID systems · optimal control · trajectory tracking · robot stabilization · nonholonomic systems. Frequently Used Symbols K(t)Feedback control gain at time t H K Hamiltonian's gradient with respect to K s Number of RFID tags in the environment ψ Costate variable (Lagrange multiplier)Robot's actual and desired pose at time t q j t ∈ R 3 jth tag position in 3D space t 0 ,t f Initial and final time instantsRobot's control input vector at time t ξ (t) Robot's actuator noise at time t ζ (t)Measurement noise vector at time t (·) o , (·) ε , (·) ad Optimal, perturb, admissible value of (·) L Lebesgue measurable function space ν T dJ(·) Gateaux (directional) derivative of J in direction ν 1 Introduction

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A Simple Adaptive Control Approach for Trajectory Tracking of Electrically Driven Nonholonomic Mobile Robots

Cited by 221 publications

References 26 publications

Neural network-based adaptive tracking control for a nonholonomic wheeled mobile robot with unknown wheel slips, model uncertainties, and unknown bounded disturbances

Neural network-based adaptive tracking control for a nonholonomic wheeled mobile robot with unknown wheel slips, model uncertainties, and unknown bounded disturbances

Linear Time-Varying Feedback Law for Vehicles With Ackermann Steering

RFID-Based Mobile Robot Trajectory Tracking and Point Stabilization Through On-line Neighboring Optimal Control

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